Qualification: 
Ph.D
prema@amrita.edu

Chancellor Amma’s vision to provide holistic Education in K12 and higher education that integrates both life and living skills along with managing health in rural India was the inspiration for AmritaCREATE (Amrita Center for Research in Analytics & Technologies for Education) at Amrita Vishwa Vidyapeetham.

Dr. Prema Nedungadi is a founding Director at AmritaCREATE (Amrita Center for Research in Analytics & Technologies for Education), an award winning, educational and health technology for societal benefit initiative of Amrita Vishwa Vidyapeetham, with $4.6m in research funding, 2 patents and over 54 publications. AmritaCREATE was selected to be one of five finalist teams for the $7M Barbara Bush Foundation's Adult Literacy XPRIZE in an awards ceremony on June 25, 2018, in New Orleans.

She is recipient of the Digital India Award from the Hon’ble Minister of MeitY, in the Category – Digital Empowerment (2015). Other awards include best journal paper, IEEE Transactions in Education (2014), Best Exhibit, Kerala Science Congress (2012), IT Excellence Award for eLearning and Education, Computer Society of India, (2013).

Her research focus areas include Education & Health Systems. AmritaCREATE has pioneered technology enhanced learning for K12 Schools & Higher Education in both formal and informal settings and in Health Awareness and Monitoring Systems. Large scale projects developed and deployed across India include Amrita Rural India Tablet enhanced Education (RITE) in remote villages, Intelligent Tutoring Systems for School Education, eGovernance Systems for Schools, Big Data Analytics in Education, Health Awareness and Monitoring IoT based Systems and Simulations and CASE Based environments for Medical Education. Her prior experience includes 15 years of Software Architecture experience at Sybase Inc. and Redbrick Systems (IBM), California, USA.

Dr. Prema Nedungadi has presented Amrita’s Digital India and Sustainable Development projects at international forums such as UNESCO and the Vatican and participated as a member of MHRD’s expert committee for inputs into the use of ICT in India’s new Education Policy. The technology and methodology is deployed in 22 states across India, with impact at 4357 schools and via. 41 remote and rural village centers. The impact includes 11,000 teachers trained and 300,000+ students impacted in schools and universities.

WORK and RESEARCH EXPERIENCE

YEAR AFFILIATION
2005 - Present Director, Amrita Center for Research in Analytics & Technologies for Education (CREATE)
Amrita Vishwa Vidyapeetham, India Visit Facebook Page »»
1998 - 2004 Founder, Successful Bay Area Consulting with focus on ERP and Internet Technologies
Clarion Technologies, California, USA
1995 - 1998 Project Manager, Red Brick Data Warehouse for Massively Parallel Systems
Redbrick Data Warehouse (acquired by IBM), California, USA
1991 - 1995 Architect, Parallel Data Server Group
Sybase Inc, USA

RESEARCH PROJECTS

  • Principal Investigator: Amrita RITE (Rural India Tablet enhanced Education)
    Funding: Amrita Vishwa Vidyapeetham
    Under Chancellor Amma’s guidance, a unique patent pending tablet technology has been developed in multiple Indian languages with the goal of providing life-changing sustainable development solutions to the disadvantaged. We work with low achieving or out of school students directly in their village settings by using after school tutoring, alternative schools and pre-schools in formal and informal settings.
    In 40 villages, Education Centers have been established, offering holistic education, blending innovative tablet technology with time tested traditional methods including academics, health awareness, social awareness, value education while taking care of their nutrition and health. Selected student Ambassadors help raise health and social awareness in the entire village.
    Impact: 22 states, 140 villages

  • Principal Investigator: eGovernance big data Analytics Platform for CBSE Schools (eGAP)
    Funding: World Bank
    Impact: Central Board for Secondary Education (CBSE), India with 15000+ schools in India 
    World Bank Funding for Amrita CREATE and School of Business for their eGovernance BigData Analytics Platform

  • Principal Investigator: Online Labs for School Practical Science (OLabs)
    Funding: eLearning Division, Department of Electronics & Information Technology (DeitY), Government of India
    The Online Labs (OLabs) for Science Practical Skills (Grades 9-12), offered free to schools, was developed to overcome the limitations faced by schools in India, especially rural schools, due to either insufficient time or instruments in laboratories. The OLabs projects reached a significant milestone in 2012, when it was officially endorsed by the Central Board of Secondary Education (CBSE) for its 15,000 schools.
    Impact: Over 60,000 secondary school students and 4,300 teachers trained.

  • Principal Investigator: Measuring Learning
    Funding: HP Foundation, USA
    Develop methods to assess STEM (Science, Technology, Engineering and Math) skills including innovation, creative and higher-order thinking, global collaboration and the ability to tackle big, open-ended challenges; these are often not evaluated in schools.
    Collaboration: Carnegie Mellon University
    Impact: 28 schools with over50,000 students
    Awarded at HP-Catalyst Summit in Beijing

  • Principal Investigator: AmritaJeevanam - Health Awareness & Monitoring Platform for Rural India
    Funding: Amrita Vishwa Vidyapeetham
    ChancellorAmma’s vision to provide low cost medical devices to villagers, train them in using it and provide health awareness, monitoring and preventive education,has resulted in AmritaJeevanam, a patent pendinglow cost solution.
    Impact: Health Monitoring & Awareness in Rural India, Health Worker Training in140 villages

  • Principal Investigator: Medical Simulation (MedSim)
    Funding: eLearning Division, DeiTY, Government of India
    MedSim is an innovative Medical Simulation Serious Game Platformthat allows medical students to visualize, learn, practise and experience a variety of medical skills and procedures. We are collaborating with Amrita Institute of Medical Sciences and Research Centre, CDAC and Trivandrum Medical College
    Impact: 200 Medical and Nursing Colleges in India

  • Principal Investigator: Continuous & Comprehensive Evaluation for Schools (CCE)
    Funding: eLearning Division, DeitY, Government of India
    Impact: Teachers and Administrators of Secondary Schools, India.

  • Co-Principal Investigator: Virtual Labs Simulation Labs for Higher Education (Physical and Chemical Sciences)
    Funding: MHRD, Government of India
    Developed over 200 virtual simulations, animations and videos in Physical Sciences, Chemical Sciences and Biotechnology. Our videos selected by prestigious youtube edu channel
    Impact: Higher Education Engineering and Science students in India.

  • Principal Investigator: Career, Soft skills & Language Labs
    Funding: Amrita Vishwa Vidyapeetham
    Caree, SoftSkill & Language Labs for job readiness for university students.
    Impact: 2000 students in India.

  • Principal Investigator: Amrita Learning Systems for Schools
    Funding: Amrita Vishwa Vidyapeetham
    Amrita Learning, our flagship product, is an Intelligent Tutoring System with Science, Language Arts and Mathematics
    Impact: 35 schools with over 36,000 students in India 

  • Principal Investigator: eLiteracy & Health Awareness using tablets for Tribals in Kerala
    Funding: IT For Masses, DeitY, Government of India
    Computer and Health Awareness using Tablets
    Impact: 1000 Scheduled Tribes in Tribal areas including abused girls.

  • Principal Investigator: Scaling of OLabs
    Funding: eLearning Division, DeitY, Government of India
    Impact: 15000 schools, training of 30,000 teachers and cloud technology for 3.6 million students

ACADEMICS

TEACHING STUDENT MENTORING INTERNATIONAL STUDENT MENTORING
M. Tech. Computer Science
M. Tech. E- learning Technology
Rural Internship
Amrita Rural Internships across India
Live-in-Labs
For more details »»

AWARDS & ACHIEVEMENTS

PATENTS

  • Filed: Two

CONFERENCES ORGANISED 

PUBLICATIONS

Year of Publication
Title

2018

P. Prof. Nedungadi, Menon, R., Gutjahr, G., Erickson, L., and Raghu Raman, “Towards an Inclusive Digital Literacy Framework for Digital India”, Education and Training, 2018.[Abstract]

Purpose: The purpose of this paper is to illustrate an Inclusive Digital Literacy Framework for vulnerable populations in rural areas under the Digital India program. Key challenges include addressing multiple literacies such as health literacy, financial literacy and eSafety for low-literate learners in low-resource settings with low internet bandwidth, lack of ICT facilities and intermittent electricity. Design/methodology/approach: This research implemented an educational model based on the proposed framework to train over 1,000 indigenous people using an integrated curriculum for digital literacies at remote settlements. The model uses mobile technology adapted for remote areas, context enabled curriculum, along with flexible learning schedules. Findings: The education model exemplifies a viable strategy to overcome persistent challenges by taking tablet-based digital literacies directly to communities. It engages different actors such as existing civil societies, schools and government organizations to provide digital literacy and awareness thereby improving both digital and life skills. It demonstrates the potential value of a comprehensive Digital Literacy framework as a powerful lever for Digital Inclusion. Practical Implications: Policy makers can use this transformational model to extend the reach and effectiveness of Digital Inclusion through the last mile enhancing existing training and service centers that offer the traditional model of Digital Literacy Education. Originality/value: This innovative mobile learning model based on the proposed Digital Framework for Inclusion instilled motivation, interest and confidence while providing effective digital training and conducting exams directly in the tribal settlements for low-literate learners in remote settings. Through incorporating multiple literacies, this model serves to empower learners, enhance potential, improve well-being and reduce the risk of exploitation. © 2018, Emerald Publishing Limited.

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2018

M. Haridas, Prof. Nedungadi, P., and Raghu Raman, “Incorporating CTML Principles in Tablet-based Learning”, in Proceedings of 2017 IEEE International Conference on Technological Advancements in Power and Energy: Exploring Energy Solutions for an Intelligent Power Grid, TAP Energy 2017, 2018.[Abstract]

The Cognitive Theory of Multimedia Learning (CTML) offers insights on creating, organizing and presenting multimedia content in a way that can enhance the effectiveness of learners. While several studies have been conducted to verify these principles, not many have been done using content presented on low cost tablets. In this paper, we present our experimental study on the retention and understanding by children when learning content a) adheres to CTML and b) offered on low cost tablets. In our study we used Online Labs theory and videos and incorporated CTML principles into it. According to CTML principle it will maximize learning without causing cognitive overload. The study sample was 58 students from an English medium secondary education school from south India. The experiment involves a control and experiment group where the control group is tested on content which does not adhere to CTML and the experimental group is tested on content designed based on CTML. A pre-test is conducted to assess the level of pre-knowledge in the subject and a post-test is conducted to assess the retention and understanding by students. This suggests that tablet content incorporated with CTML principle can lead to a deeper understanding of the subject.

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2018

P. Prof. Nedungadi, Iyer, A., Gutjahr, G., Bhaskar, J., and Pillai, A. B., “Data-Driven Methods for Advancing Precision Oncology”, Current Pharmacology Reports, vol. 4, pp. 145-156, 2018.[Abstract]

Purpose of Review: This article discusses the advances, methods, challenges, and future directions of data-driven methods in advancing precision oncology for biomedical research, drug discovery, clinical research, and practice. Recent Findings: Precision oncology provides individually tailored cancer treatment by considering an individual’s genetic makeup, clinical, environmental, social, and lifestyle information. Challenges include voluminous, heterogeneous, and disparate data generated by different technologies with multiple modalities such as Omics, electronic health records, clinical registries and repositories, medical imaging, demographics, wearables, and sensors. Statistical and machine learning methods have been continuously adapting to the ever-increasing size and complexity of data. Precision Oncology supportive analytics have improved turnaround time in biomarker discovery and time-to-application of new and repurposed drugs. Precision oncology additionally seeks to identify target patient populations based on genomic alterations that are sensitive or resistant to conventional or experimental treatments. Predictive models have been developed for cancer progression and survivorship, drug sensitivity and resistance, and identification of the most suitable combination treatments for individual patient scenarios. In the future, clinical decision support systems need to be revamped to better incorporate knowledge from precision oncology, thus enabling clinical practitioners to provide precision cancer care. Summary: Open Omics datasets, machine learning algorithms, and predictive models have enabled the advancement of precision oncology. Clinical decision support systems with integrated electronic health record and Omics data are needed to provide data-driven recommendations to assist clinicians in disease prevention, early identification, and individualized treatment. Additionally, as cancer is a constantly evolving disorder, clinical decision systems will need to be continually updated based on more recent knowledge and datasets.

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2018

A. Radhakrishnan, Pillai, N. M., Bhavani, R. R., Gutjahr, G., and Prof. Nedungadi, P., “Awareness and Effectiveness of Educational Schemes for Scheduled Caste and Scheduled Tribes in Coimbatore District”, International Journal of Pure and Applied Mathematics, vol. 119, pp. 1933-1941, 2018.[Abstract]

Educational schemes for marginalized communities such as SC/ST were introduced by the Government of India with the aim of providing equal opportunity for scheduled tribe and scheduled caste to empower them with free educational facilities. For such programs to be effective, SC/ST members need to be aware of them and need to have a positive attitude towards them. However, due to the practice of untouchability and the remoteness of their dwellings, SCs and STs have suffered isolation from mainstream population for several centuries. As a consequence, they continue to suffer from a high degree of educational exclusion. Upliftment of SCs and STs, both economically and socially, will be only possible through inclusive education efforts. This study focus on the role ofawareness on educational schemes in attaining primary and secondary education among SC/ST communities in two rural villages in Coimbatore. The major findings of the study reveals that most of marginalized communities continue to remain unaware of the educational schemes and are unable to utilize all the provisions of the schemes. © 2018 Academic Press.

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2018

P. Prof. Nedungadi, Dr. Maneesha V. Ramesh, Pradeep, P., and Raghu Raman, “Pedagogical Support for Collaborative Development of Virtual and Remote Labs: Amrita VLCAP”, in Cyber-Physical Laboratories in Engineering and Science Education, M. E. Auer, Azad, A. K. M., Edwards, A., and de Jong, T. Cham: Springer International Publishing, 2018, pp. 219–240.[Abstract]

There is an explosive growth in e-Learning platforms, jointly developed by multiple institutions, which provide for virtual learning content. However, many are inadequate to support the complex requirements for collaborative development of distributed learning such as accommodation of wide-ranging technologies, servers, and remote equipment controlled by diverse software. Our solution is a multi-tier architecture that supports collaborative development, publishing in various online and print formats, security, audit, and access controls. Our design considerations include a highly scalable platform, use of open technologies, templates that provide pedagogical structure, multilingual functionality, and shared virtual availability of lab equipment from multiple geographic locations, along with secure access to remote equipment.

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2017

P. Prof. Nedungadi, Raghu Raman, Menon, R., and Mulki, K., “AmritaRITE: A Holistic Model for Inclusive Education in Rural India”, in Children and Sustainable Development: Ecological Education in a Globalized World, A. M. Battro, Léna, P., Sorondo, M. Sánchez, and von Braun, J. Cham: Springer International Publishing, 2017, pp. 171–184.

2017

P. Prof. Nedungadi, Mulki, K., and Raghu Raman, “Improving educational outcomes & reducing absenteeism at remote villages with mobile technology and WhatsAPP: Findings from rural India”, Education and Information Technologies, pp. 1–15, 2017.[Abstract]

Reduction of teacher and student absenteeism, together with consistent teacher support and training, are critical factors in improving the quality of education in rural India. As part of an ongoing project involving schools and educational centers in rural areas spread across 21 Indian states, this study investigated how implementation of two simple, accessible technologies could not only reduce absenteeism but also increase teachers' effectiveness and improve student performance. In addition to students and teachers, key stakeholders included educational coordinators who provided support and monitoring regarding use of WhatsApp and two additional apps designed specifically to support simple educational improvements. In our study we coded and analyzed nine months of messages (nþinspace}=þinspace}8968), both photographs and texts, posted by 26 participants. The number of text messages related to attendance was strongly positively correlated with frequency of interactions between coordinators and teachers. Our approach resulted in increased teacher and student attendance, as well as improvements in lessons and other planned educational activities. This model functions well in rural settings where there is poor internet connectivity and lack of supporting infrastructure. Remote schools can easily adopt this tablet-based model to reduce teacher absenteeism, improve teaching techniques, improve educational resources, and increase student performance.

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PDF iconimproving-educational-outcomes-reducing-absenteeism-at-remote-villages-with-mobile-technology-and-whatsappfindings-from-rural-india.pdf

2017

P. Prof. Nedungadi, Jayakumar, A., and Raghu Raman, “Personalized Health Monitoring System for Managing Well-Being in Rural Areas.”, J Med Syst, vol. 42, no. 1, p. 22, 2017.[Abstract]

Rural India lacks easy access to health practitioners and medical centers, depending instead on community health workers. In these areas, common ailments that are easy to manage with medicines, often lead to medical escalations and even fatalities due to lack of awareness and delayed diagnosis. The introduction of wearable health devices has made it easier to monitor health conditions and to connect doctors and patients in urban areas. However, existing initiatives have not succeeded in providing adequate health monitoring to rural and low-literate patients, as current methods are expensive, require consistent connectivity and expect literate users. Our design considerations address these concerns by providing low-cost medical devices connected to a low-cost health platform, along with personalized guidance based on patient physiological parameters in local languages, and alerts to medical practitioners in case of emergencies. This patient-centric integrated healthcare system is designed to manage the overall health of villagers with real-time health monitoring of patients, to offer guidance on preventive care, and to increase health awareness and self-monitoring at an affordable price. This personalized health monitoring system addresses the health-related needs in remote and rural areas by (1) empowering health workers in monitoring of basic health conditions for rural patients in order to prevent escalations, (2) personalized feedback regarding nutrition, exercise, diet, preventive Ayurveda care and yoga postures based on vital parameters and (3) reporting of patient data to the patient's health center with emergency alerts to doctor and patient. The system supports community health workers in the diagnostic procedure, management, and reporting of rural patients, and functions well even with only intermittent access to Internet.

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2017

R. Menon, Prof. Nedungadi, P., and Raghu Raman, “Technology Enabled Teacher Training for Lowliterate, Remote and Rural Multi-grade Education Centers”, in 2017 International Conference on Advances in Computing, Communications and Informatics, ICACCI 2017, 2017.[Abstract]

In remote rural areas, the availability of trained and qualified teachers is poor. Rural teaching is teachercentric instead of student-centric. A systematic monitoring system to ensure that teachers practice the methods they learn at pre- or in-service trainings is not yet in place. Plagued by such deficiencies, present day rural education in India lacks quality, and children read, write, and compute several levels below grade level. Our intervention comes from the premise that reform approach in rural education should be at the grassroots level, involving comprehensive change in teaching and learning attitudes, teaching methodology and subject matter expertise. Amrita Rural India Tablet Education Teacher Training Program is a technology-enabled training program for teachers that train them to be change-agents and influence both children and communities to bring about sustainable change in attitudes as well as education and learning outcomes. AmritaRITE utilizes cutting edge mobile learning technology in both teaching and monitoring, to improve quality and accountability, even in low-electricity and intermittent-connectivity areas. The comprehensive program trains teachers in tablet-supported teaching methodologies, multi-age classrooms, classroom management styles suited to specific environment, addressing different learning modalities, developing student critical thinking, identifying learning disabilities and overcoming social barriers such as educating girls and low literacy communities.

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2017

V. Pavithran, Raj, A. S., Prof. Nedungadi, P., and Achuthan, K., “Hello World: Bootstrapping Cybersecurity Education in Indian Rural High Schools”, in 2017 IEEE Frontiers in Education Conference (FIE), 2017.

2016

Dr. Shyam Diwakar, Dhanush Kumar, Radhamani, R., Sasidharakurup, H., Nizar, N., Dr. Krishnashree Achuthan, Prof. Nedungadi, P., Raghu Raman, and Dr. Bipin G. Nair, “Complementing Education via Virtual Labs: Implementation and Deployment of Remote Laboratories and Usage Analysis in South Indian Villages”, International Journal of Online Engineering (iJOE), vol. 12, no. 03, 2016.[Abstract]

ICT-enabled virtual and remote labs have become a platform augmenting user engagement in blended education scenarios enhancing University education in rural India.
A novel trend is the use of remote laboratories as learning and teaching tools in classrooms and elsewhere. This paper reports case studies based on our deployment of 20 web-based
virtual labs with more than 170+ online experiments in Biotechnology and Biomedical engineering discipline with content for undergraduate and postgraduate education.

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PDF iconcomplementing-education-via-virtual-labs-implementation-and deployment-of-emote-laboratories-and-usage-analysis-in-south-indian-villages.pdf

2016

A. Jayakumar, Babu, G. S., Raghu Raman, and Prof. Nedungadi, P., “Integrating Writing Direction and Handwriting Letter Recognition in Touch-Enabled Devices”, in Integrating Writing Direction and Handwriting Letter Recognition in Touch-Enabled Devices, vol. 380, New Delhi: Springer India, 2016, pp. 393–400.[Abstract]

Optical character recognition (OCR) transforms printed text to editable format and digital writing on smart devices. Learning to write programs has made learners trace an alphabet to learn the flow of writing and OCR by itself is less effective as it ignores the directional flow of writing and only focuses on the final image. Our research designed a unique android-based multilingual game-like writing app that enhances the writing experience. A key focus of the research was to compare and identify character recognition algorithms that are effective on low-cost android tablets with limited processing capabilities. We integrate a quadrant-based direction checking system with artificial neural networks and compare it to the existing systems. Our solution has the dual advantage of evaluating the writing direction and significantly increasing the accuracy compared to the existing systems. This program is used as the literacy tool in many villages in rural India.

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PDF iconintegrating-writing-direction-and-handwriting-letter-recognition-in-touch-enabled-devices.pdf

2016

P. Prof. Nedungadi and Raghu Raman, “The medical virtual patient simulator (MedVPS) platform”, Advances in Intelligent Systems and Computing, vol. 384, pp. 59-67, 2016.[Abstract]

Medical Virtual Patient Simulator (MedVPS) is a cutting-edge eLearning innovation for medical and other health professionals. It consists of a framework that supports various patient cases, tailored by interdisciplinary medical teams. Each virtual patient case follows the critical path to be followed for a specific patient in a hospital. MedVPS takes the student on a journey that enables the student to interview, examine, conduct physical, systematic and ultimately reach a diagnosis based on the path that is chosen. After the interactions, the student must decide whether each response is normal or abnormal and use the virtual findings to identify multiple probable diagnoses or reexamine the virtual patient with the goal to narrow down to the correct disease and then provide treatment. We present the architecture and functionality of the MedVPS platform and include a pilot study with medical students. © Springer International Publishing Switzerland 2016.

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PDF iconthe-medical-virtual-patient-simulator-medvps-platform.pdf

2016

P. Prof. Nedungadi and Smruthy, T. K., “Enhanced Higher Order Orthogonal Iteration Algorithm for Student Performance Prediction”, in Proceedings of the Second International Conference on Computer and Communication Technologies: IC3T 2015, Volume 1, S. Chandra Satapathy, K. Raju, S., Mandal, J. Kumar, and Bhateja, V. New Delhi: Springer India, 2016, pp. 639–649.[Abstract]

Predicting Student Performance is the process that predicts the successful completion of a task by a student. Such systems may be modeled using a three-mode tensor where the three entities are user, skill, and task. Recommendation systems have been implemented using Dimensionality reduction techniques like Higher Order Singular Value Decomposition (HOSVD) combined with Kernel smoothing techniques to bring out good results. Higher Order Orthogonal Iteration (HOOI) algorithms have also been used in recommendation systems to bring out the relationship between the three entities, but the prediction results would be largely affected by the sparseness in the tensor model. In this paper, we propose a generic enhancement to HOOI algorithm by combining it with Kernel smoothing techniques. We perform an experimental comparison of the three techniques using an ITS dataset and show that our proposed method improves the prediction for larger datasets.

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PDF iconenhanced-higher-order-orthogonal-iteration-algorithm-for-student-performance-prediction.pdf

2016

P. Prof. Nedungadi and Smruthy, T. K., “Personalized Multi-relational Matrix Factorization Model for Predicting Student Performance”, in Intelligent Systems Technologies and Applications: Volume 1, S. Berretti, Thampi, S. M., and Srivastava, P. Ranjan Cham: Springer International Publishing, 2016, pp. 163–172.[Abstract]

Matrix factorization is the most popular approach to solving prediction problems. However, in the recent years multiple relationships amongst the entities have been exploited in order to improvise the state-of-the-art systems leading to a multi relational matrix factorization (MRMF) model. MRMF deals with factorization of multiple relationships existing between the main entities of the target relation and their metadata. A further improvement to MRMF is the Weighted Multi Relational Matrix Factorization (WMRMF) which treats the main relation for the prediction with more importance than the other relations. In this paper, we propose to enhance the prediction accuracy of the existing models by personalizing it based on student knowledge and task difficulty. We enhance the WMRMF model by incorporating the student and task bias for prediction in multi-relational models. Empirically we have shown using over five hundred thousand records from Knowledge Discovery dataset provided by Data Mining and Knowledge Discovery competition that the proposed approach attains a much higher accuracy and lower error(Root Mean Square Error and Mean Absolute Error) compared to the existing models.

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PDF iconpersonalized-multi-relational-matrix-factorization-model-for-predicting-student-performance.pdf

2016

A. Jayakumar, Raghunath, M., S, S. M., S, A., Sadanandan, A., and Prof. Nedungadi, P., “Enhancing speech recognition in developing language learning systems for low cost Androids”, in 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), 2016.[Abstract]

Learning to read correctly is a key requirement of language learning. In rural India, due to lack of teachers and technology, tablets offer a creative and motivating learning environment. Tablet technology has the advantage of mobility, allowing users to learn at their own pace and convenience. However, the non-availability of electricity and Internet can be unique challenges. At Amrita CREATE, language-learning solutions have been developed for students to learn and read on the tablets. It uses advanced speech recognition technique to provide feedback and intervention. Proposed system is unique in its ability to evaluate words and phrases and corrects the learner as they articulate the sentence. This system works without Internet and on the lower processing power of android tablets. Silence detection and multiple-synchronized recognition have been introduced in this paper which greatly enhance the ability to provide feedback to the user in real-time. The combination of the two helps in achieving successful recognition of longer and continuous sentence.

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PDF iconenhancing-speech-recognition-in-developing-language-learning-systems-for-low-cost-androids.pdf

2016

H. Haripriya, Cp, P., Pai, Y. R., Sandeep, M. S., Sankar, A. M., a, S. N. V., and Prof. Nedungadi, P., “Multi label prediction using association rule generation and simple k-means”, in 2016 International Conference on Computational Techniques in Information and Communication Technologies (ICCTICT), 2016.[Abstract]

Lately, modern applications like information retrieval, semantic scene classification, music categorization and functional genomics classification highly require multi label classification. A rule mining algorithm apriori is widely used for rule generation. But Apriori is used many times on categorical data, it is seldom used for numerical data. This leads to an idea that with proper data pre-processing, a lot of intangible rules can be derived from such numerical datasets. Since the algorithm will check each and every datasets, we used a simple k-means clustering approach for dividing the processing space of Apriori and thus rules are generated for each cluster. The accuracy of the algorithm is calculated using hamming loss and is presented in the paper. This hybrid algorithm directly aims to find out hidden patterns in huge numerical datasets and make reliable label prediction easier.

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PDF iconmulti-label-prediction-using-association-rule-generation-and-simple-k-means.pdf

2016

P. Prof. Nedungadi and Haripriya, H., “Feature and Search Space Reduction for Label-Dependent Multi-label Classification”, in Proceedings of the Second International Conference on Computer and Communication Technologies: IC3T 2015, Volume 2, S. Chandra Satapathy, K. Raju, S., Mandal, J. Kumar, and Bhateja, V. New Delhi: Springer India, 2016, pp. 591–599.[Abstract]

The problem of high dimensionality in multi-label domain is an emerging research area to explore. A strategy is proposed to combine both multiple regression and hybrid k-Nearest Neighbor algorithm in an efficient way for high-dimensional multi-label classification. The hybrid kNN performs the dimensionality reduction in the feature space of multi-labeled data in order to reduce the search space as well as the feature space for kNN, and multiple regression is used to extract label-dependent information from the label space. Our multi-label classifier incorporates label dependency in the label space and feature similarity in the reduced feature space for prediction. It has various applications in different domains such as in information retrieval, query categorization, medical diagnosis, and marketing.

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PDF iconfeature-and-search-space-reduction-for-label-dependent-multi-label-classification.pdf

2015

P. Prof. Nedungadi, Malini, P., and Raghu Raman, “Inquiry based learning pedagogy for chemistry practical experiments using OLabs”, Advances in Intelligent Systems and Computing, vol. 320, pp. 633-642, 2015.[Abstract]

Our paper proposes a new pedagogical approach for learning chemistry practical experiments based on three modes of inquiry-based learning namely; structured, guided and open. Online Labs (OLabs) is a web-based learning environment for science practical experiments that include simulations, animations, tutorials and assessments. Inquiry-based learning is a pedagogy that supports student-centered learning and encourages them to think scientifically. It develops evidence based reasoning and creative problem solving skills that result in knowledge creation and higher recall. We discuss the methodology and tools that OLabs provides to enable educators to design three types of inquiry-based learning for Chemistry experiments. The integration of inquiry-based learning into OLabs is aligned with the Indian Central Board of Secondary Education (CBSE) goal of nurturing higher order inquiry skills for student centered and active learning. Inquiry-based OLabs pedagogy also empowers the teachers to provide differentiated instruction to the students while enhancing student interest and motivation. © Springer International Publishing Switzerland 2015.

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PDF iconinquiry-based-learning-pedagogy-for-chemistry-practical-experiments-using-o-labs.pdf

2015

Raghu Raman, Haridas, M., and Prof. Nedungadi, P., “Blending Concept Maps with Online Labs for STEM Learning”, Advances in Intelligent Systems and Computing, vol. 320, pp. 133-141, 2015.[Abstract]

In this paper we describe the architecture of an e-learning environment that blends concept maps with Online Labs (OLabs) to enhance student performance in biology. In the Indian context, a secondary school student’s conceptual understanding of hard topics in biology is at risk because of a lack of qualified teachers and necessary equipments in labs to conduct experiments. Concept map provides a visual framework which allows students to get an overview of a concept, its various sub concepts and their relationships and linkages. OLabs with its animations, videos and simulations is an interactive, immersive approach for practicing science experiments. The blended e-learning environment was tested by systematically developing a concept map for the concept “Photosynthesis” and by successfully integrating it into the OLabs environment. Our blended approach to concept understanding has interesting implications for the teacher who is engaged in training programs.

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PDF iconblending-concept-maps-with-online-labs-for-stem-learning-1.pdf

2015

P. Prof. Nedungadi and Remya, M. S., “Incorporating forgetting in the Personalized, Clustered, Bayesian Knowledge Tracing (PC-BKT) model”, in Cognitive Computing and Information Processing (CCIP), 2015 International Conference on, Noida, 2015.[Abstract]

Personalization and adaptation are at the core of Intelligent Tutoring Systems. The Bayesian Knowledge Tracing (BKT) Student Model is a time-tested method that maintains information about students' knowledge levels for the different skills in the topic domain. In our previous work, we had proposed the Personalized, Clustered, Bayesian Knowledge Tracing (PC-BKT) model that individualizes the learning of skills for each student and additionally improves the prediction for the cold start problem. A clustering of both students and skills based on a student and skill capability matrix was used to learn the prior skills to deal with the cold start problem, which is the prediction for either new skills or new students. Both the BKT and the PC-BKT models assume that a skill once learnt is never forgotten. But forgetting is pervasive. If a previously learnt skill is not used for a while, there is a higher chance of forgetting it. One of the factors that influence the forgetting is the time duration before the current attempt at using a skill and the previous attempt. We incorporate forgetting as a time decay function in the BKT and PC-BKT models and show significant increase in the accuracy of the student prediction.

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PDF iconincorporating-forgetting-in-the-personalized-clustered- bayesian-knowledge-tracing -pc-bkt-model.pdf

2015

Raghu Raman, Prof. Nedungadi, P., V Smrithi Rekha, and Krishnasree Achuthan, “Computer Science (CS) Education in Indian Schools: Situation Analysis using Darmstadt Model”, ACM Transactions on Computing Education (IN PRESS), 2015.[Abstract]

Computer science (CS) and its enabling technologies are at the heart of this information age, yet its adoption as a core subject by senior secondary students in Indian schools is low and has not reached critical mass. Though there have been efforts to create core curriculum standards for subjects like Physics, Chemistry, Biology, and Math, CS seems to have been kept outside the purview of such efforts leading to its marginalization. As a first step, using the Darmstadt model from the ITiCSE working group that provides a systematic categorization approach to CS education in schools, we coded and analyzed the CS situation for the Indian schools. Next, we focused on the motivation category of the Darmstadt model and investigated behavioral intentions of secondary school students and teachers from 332 schools in India. Considering the CS subject as an educational innovation, using Rogers’ Theory of Diffusion of Innovations, we propose a pedagogical framework for innovation attributes that can significantly predict-adoption of the CS subject among potential-adopter students and teachers. Data was analyzed to answer research questions about student and teacher intentions, influence of gender, school management, and school location in adopting CS. Interestingly, girls, urban students, teachers, and private schools were seen favoring the adoption of CS. An important issue that needed to be addressed, however, was the interchangeable use of terms like CS, Informatics, ICT, and digital literacy. Through our article, we offer a promising picture of the educational policy directives and the academic environment in India that is rapidly growing and embracing CS as a core subject of study in schools. We also analyze the factors that influence the adoption of CS by school students and teachers and conclude that there is a very positive response for CS among educators and students in India.

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PDF iconcomputer-science-cs-education-in-indian-schools-situation-analysis-using-darmstadt-model.pdf

2015

P. Prof. Nedungadi, Haridas, M., and Raghu Raman, “Blending concept maps with online labs (OLabs): Case study with biological science”, in ACM International Conference Proceeding Series, 2015, vol. 10-13-August-2015, pp. 186-190.[Abstract]

Experimental learning combined with theoretical learning enhances the conceptual understanding of a subject. Therefore, the Online Labs (OLabs) that hosts science experiments was developed. OLabs uses interactive simulations with theory, procedure, animations, videos, assessments and reference material. Our study blended OLabs with concept maps to examine if it enhances students' learning in Biology. Concept mapping is a framework that provides a deeper knowledge of a subject by understanding the relationships among concepts. The study was quasi-experimental; pre-test, post-test and a satisfaction survey was used as measurement instruments. The study sample was 54 students from a school in Haripad, Kerala, India. The students were randomly grouped into a control and an experimental group. The experimental group that used concept maps as a learning aid scored slightly higher, suggesting blending concept maps can lead to a deeper understanding of the subject. Gender difference did not significantly affect the scores. © 2015 ACM.

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PDF iconblending-concept-maps-with-online-labs-olabs-case-study-with-biological-science.pdf

2015

Raghu Raman, Dr. Krishnashree Achuthan, Prof. Nedungadi, P., Dr. Shyam Diwakar, and Bose, R., “The VLAB OER Experience: Modeling Potential-Adopter Students' Acceptance”, IEEE Transactions on Education, vol. 57, pp. 235–241, 2015.[Abstract]

Virtual Labs (VLAB) is a multi-institutional Open Educational Resources (OER) initiative, exclusively focused on lab experiments for engineering education. This project envisages building a large OER repository, containing over 1650 virtual experiments mapped to the engineering curriculum. The introduction of VLAB is a paradigm shift in an educational system that is slow to change. Treating VLAB OER as an educational technology innovation, its adoption by potential-adopter engineering students (N=131) is modeled based on Roger's theory of perceived attributes. Regression and factor analysis were used to analyze the data. Results indicate that the attributes of Compatibility, Ease of Use, Relative Advantage, and Trialability significantly influence potential-adopter students' intention to adopt an innovation like VLAB. The study also observed that using OER (such as VLAB) on desktops and low-cost tablets had similar effects in student performance to using physical labs. This has interesting implications for education policy-makers who are looking to reduce the digital divide.

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PDF iconvlab-oer-experience-modeling-potential-adopter-students-acceptance.pdf

2015

J. Bhaskar, Sruthi, K., and Prof. Nedungadi, P., “Hybrid approach for emotion classification of audio conversation based on text and speech mining”, in Procedia Computer Science, 2015.[Abstract]

This paper examines the dynamics of access and exclusion in children’s Internet use, in both private and public school spaces and interrogates the role of socioeconomic and demographic predictors as well as the schooling system in shaping Internet habits. More specifically, it explores the nature of Internet use by primary school children, mainly for education and information and attempts to understand the differences across and within two types of schools- a rural public school and an elite private school. Through in-depth interviews, this research investigates the level of computer and Internet literacy among the primary school children in the age group of 8-10 years and reports the differences observed among the various social dimensions. It attempts to stress the significance and need in today’s context to provide the opportunities for physical and material access so that disadvantaged children are not excluded from the digital opportunities. © Media Watch.

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PDF iconhybrid-approach-for-emotion-classification-of-audio-conversation-based-on-text-and-speech-mining.pdf

2015

P. Prof. Nedungadi, Malini, P., and Raghu Raman, “Inquiry Based Learning Pedagogy for Chemistry Practical Experiments Using OLabs”, in Advances in Intelligent Informatics, Springer, 2015, pp. 633–642.[Abstract]

Our paper proposes a new pedagogical approach for learning chemistry practical experiments based on three modes of inquiry-based learning namely; structured, guided and open. Online Labs (OLabs) is a web-based learning environment for science practical experiments that include simulations, animations, tutorials and assessments. Inquiry-based learning is a pedagogy that supports student-centered learning and encourages them to think scientifically. It develops evidence based reasoning and creative problem solving skills that result in knowledge creation and higher recall. We discuss the methodology and tools that OLabs provides to enable educators to design three types of inquiry-based learning for Chemistry experiments. The integration of inquiry-based learning into OLabs is aligned with the Indian Central Board of Secondary Education (CBSE) goal of nurturing higher order inquiry skills for student centered and active learning. Inquiry-based OLabs pedagogy also empowers the teachers to provide differentiated instruction to the students while enhancing student interest and motivation.

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PDF iconinquiry-based-learning-pedagogy-for-chemistry-practical-experiments-using-olabs.pdf

2015

Raghu Raman, Haridas, M., and Prof. Nedungadi, P., “Blending Concept Maps with Online Labs for STEM Learning”, in Advances in Intelligent Informatics, Springer, 2015, pp. 133-141.[Abstract]

In this paper we describe the architecture of an e-learning environment that blends concept maps with Online Labs (OLabs) to enhance student performance in biology. In the Indian context, a secondary school student’s conceptual understanding of hard topics in biology is at risk because of a lack of qualified teachers and necessary equipments in labs to conduct experiments. Concept map provides a visual framework which allows students to get an overview of a concept, its various sub concepts and their relationships and linkages. OLabs with its animations, videos and simulations is an interactive, immersive approach for practicing science experiments. The blended e-learning environment was tested by systematically developing a concept map for the concept “Photosynthesis” and by successfully integrating it into the OLabs environment. Our blended approach to concept understanding has interesting implications for the teacher who is engaged in training programs.

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PDF iconblending-concept-maps-with-online-labs-for-stem-learning.pdf

2015

Ha Haripriya, DeviSree, Rb, Pooja, Db, and Prof. Nedungadi, P., “A Comparative Performance Analysis of Self Organizing Maps on Weight Initializations Using different Strategies”, in Proceedings - 2015 5th International Conference on Advances in Computing and Communications, ICACC 2015, 2015, pp. 434-438.[Abstract]

Self Organizing Maps perform clustering of data based on unsupervised learning. It is of concern that initialization of the weight vector contributes significantly to the performance of SOM and since real world datasets being high-dimensional, the complexity of SOM tend to increase tremendously leading to increased time consumption as well. Our work focuses on the analysis of different weight initialization strategies and various dimensionality reduction measures with the intent to make SOM flexible for handling high-dimensional datasets. We use two methods of comparison, one on projected space and another before projection. The datasets used are real world datasets taken from UCI repository. © 2015 IEEE.

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PDF icona-comparative-performance-analysis-of-self-organizing-maps-on-weight-initializations-using-different-strategies.pdf

2015

R. Menon and Prof. Nedungadi, P., “New methodology to differentiate instructional strategies for ESL learners in the Indian context”, in 2015 IEEE Frontiers in Education Conference (FIE), 2015.[Abstract]

Many students struggle with reading when whole group instruction forms the core of the reading program. This is especially true when teaching second language students. The proposed intervention methodology combines multiple proven methods to improve reading skills in students. The study focused on using differentiated instruction and multiple assessments such as Informal Reading Inventory (IRI), Qualitative Spelling Inventory (QSI), Running Records, Dynamic Indicators of Basic Early Literacy Skills (DIBELS), High-frequency words and phonological awareness. After the usage of the said tools, students learnt to follow a firm reading routine, respect classroom procedures, work in teams and solve problems independently. This five-month study examined the benefits of the differentiated instruction with thirty six 5th grade students, who were the second language English learners in a school in the state of Karnataka, India. The key findings from this study indicated that differentiating instruction and using small group instruction assisted and improved students' reading and writing proficiency. With our proposed method, 94% of the students improved their reading comprehension by a minimum of three grade levels. An unexpected benefit was a positive change in attitude and behavior of the students along with increased confidence.

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PDF iconnew-methodology-to-differentiate-instructional-strategies-for-esl-learners-in-the-indian-context.pdf

2015

A. Jayakumar, Mathew, B., N, U., and Prof. Nedungadi, P., “Interactive Gesture Based Cataract Surgery Simulation”, in 2015 Fifth International Conference on Advances in Computing and Communications (ICACC), 2015.[Abstract]

India's medical education domain is one of the largest in the world. Medical Simulation aims to provide a medically accurate simulation that benefits the medical students to learn and understand any medical cases. Medical Simulations facilitates students with interactive learning and real-time feedback which does not risk the patient's life. Simulations can be performed any number of time until they have build their knowledge base and confidence in the given medical case. We propose a medically realistic cataract surgery simulation developed with a game engine. The users will be able to interact and use the on screen elements using hand gestures. A Motion recognition device captures every hand movement of the users and the simulation responds accordingly to provide feedback in real-time. Every movement is accurately tracked in the simulation and has a significant outcome on the subject based on the type of simulation. The simulated medical procedures for cataract surgery include using Surgical Tools, Surgical Procedures, Artificial Lens Implantation etc. Medical Simulation is being designed to provide an easy to use learning environment to replicate the clinical scenarios and allow features such as interactively practicing and providing feedbacks for medical skills development.

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PDF iconinteractive-gesture-based-cataract-surgery-simulation.pdf

2015

H. Haripriya, Amrutha, S., Veena, R., and Prof. Nedungadi, P., “Integrating Apriori with Paired K-means for Cluster Fixed Mixed Data”, in Proceedings of the Third International Symposium on Women in Computing and Informatics, New York, NY, USA, 2015.[Abstract]

The field of data mining is concerned with finding interesting patterns from an unstructured data. A simple, popular as well as an efficient clustering technique for data analysis is k-means. But classical k-means algorithm can only be applied to numerical data where k is a user given value. But the data generated from a wide variety of domains are of mixed form and it is effortful to trust on a user given value for k. So our objective is to effectively use an association rule mining algorithm which can automatically compute the number of clusters and a pairwise distance measure for calculating the distance in mixed data. We have done experimentations with real mixed data taken from the UCI repository.

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PDF iconintegrating-apriori-with-paired-k-means-for-cluster-fixed-mixed-data.pdf

2014

P. Prof. Nedungadi, L, J., and Raghu Raman, “Considering Misconceptions in Automatic Essay Scoring with A-TEST - Amrita Test Evaluation & Scoring Tool”, in AFRICOMM 2013, Springer Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST) , 2014.[Abstract]

<p>In large classrooms with limited teacher time, there is a need for automatic evaluation of text answers and real-time personalized feedback during the learning process. In this paper, we discuss Amrita Test Evaluation &amp; Scoring Tool (A-TEST), a text evaluation and scoring tool that learns from course materials and from human-rater scored text answers and also directly from teacher input. We use latent semantic analysis (LSA) to identify the key concepts. While most AES systems use LSA to compare students’ responses with a set of ideal essays, this ignores learning the common misconceptions that students may have about a topic. A-TEST also uses LSA to learn misconceptions from the lowest scoring essays using this as a factor for scoring. ‘A-TEST’ was evaluated using two datasets of 1400 and 1800 pre-scored text answers that were manually scored by two teachers. The scoring accuracy and kappa scores between the derived ‘A-TEST’ model and the human raters were comparable to those between the human raters.</p>

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PDF iconconsidering-misconceptions-in-automatic-essay-scoring-with-a-test-amrita-test-evaluation-scoring-tool.pdf

2014

Raghu Raman, Dr. Krishnashree Achuthan, Prof. Nedungadi, P., and Dr. Maneesha V. Ramesh, “Modeling Diffusion of Blended Labs for Science Experiments Among Undergraduate Engineering Students”, Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, vol. 135 LNICST, pp. 234-247, 2014.[Abstract]

While there is large body of work examining efficacy of Virtual Labs in engineering education, studies to date have lacked modeling Blended Labs (BL) - mix of Virtual Labs (VL) and Physical Labs (PL) for science experimentation at the university engineering level. Using Rogers theory of perceived attributes, this paper provides a research framework that identifies the attributes for BL adoption in a social group comprising of (N=246) potential adopter undergraduate engineering students. Using Bass model the study also accounts for the interinfluence of related group of potential adopter faculties who are likely to exert positive influence on students. The results revealed that acceptance of BL as an innovation and its learning outcomes are strongly associated with innovation attributes like Relative Advantage, Compatibility, Ease of Use, Department and Faculty support. Learning outcomes are very positive under BL when compared to PL, though within BL, ordering of PL and VL was not significant. For certain innovation attributes gender differences were significant. Overall students expressed much more positive attitude to adopt BL model for learning than using only PL. © Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2014.

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PDF iconmodeling-diffusion-of-blended-labs-for -science-experiments-among-undergraduate-engineering-students.pdf

2014

P. Prof. Nedungadi and Remya, M. Sb, “A scalable feature selection algorithm for large datasets-quick branch & bound iterative (QBB-I)”, Smart Innovation, Systems and Technologies, vol. 27, pp. 125-136, 2014.[Abstract]

Feature selection algorithms look to effectively and efficiently find an optimal subset of relevant features in the data. As the number of features and the data size increases, new methods of reducing the complexity while maintaining the goodness of the features selected are needed. We review popular feature selection algorithms such as the probabilistic search algorithm based Las Vegas Filter (LVF) and the complete search based Automatic Branch and Bound (ABB) that use the consistency measure. The hybrid Quick Branch and Bound (QBB) algorithm first runs LVF to find a smaller subset of valid features and then performs ABB with the reduced feature set. QBB is reasonably fast, robust and handles features which are interdependent, but does not work well with large data. In this paper, we propose an enhanced QBB algorithm called QBB Iterative (QBB-I).QBB-I partitions the dataset into two, and performs QBB on the first partition to find a possible feature subset. This feature subset is tested with the second partition using the consistency measure, and the inconsistent rows, if any, are added to the first partition and the process is repeated until we find the optimal feature set. Our tests with ASSISTments intelligent tutoring dataset using over 150,000 log data and other standard datasets show that QBB-I is significantly more efficient than QBB while selecting the same subset of features. © Springer International Publishing Switzerland 2014.

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PDF icona-scalable-feature-selection-algorithm-for-large-datasets-quick-branch-bound-iterative-qbb-i.pdf

2014

J. Bhaskar, Sruthi, K., and Prof. Nedungadi, P., “Enhanced sentiment analysis of informal textual communication in social media by considering objective words and intensifiers”, in IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE), 2014, Jaipur, 2014.[Abstract]

Sentiment analysis is a valuable knowledge resource to understand collective sentiments from the Web and helps make better informed decisions. Sentiments may be positive, negative or objective and the method of assigning sentiment weights to terms and sentences are important factors in determining the accuracy of the sentiment classification. We use standard methods such as Natural Language Processing, Support Vector Machines and SentiWordNet lexical resource. Our work aims at improving the sentiment classification by modifying the sentiment values returned by SentiWordNet for intensifiers based on the context to the semantic of the words related to the intensifier. We also reassign some of the objective words to either positive or negative sentiment. We test our sentiment classification method with product reviews of digital cameras gathered from Amazon and ebay and shows that our method improves the prediction accuracy.

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PDF iconenhanced-sentiment-analysis-of-informal-textual-communication-in-social-media-by-considering-objective-words-and-intensifiers.pdf

2014

P. Prof. Nedungadi and Remya, M. S., “Predicting Students’ Performance on Intelligent Tutoring System-Personalized Clustered BKT (PC-BKT) Model”, in 44th Frontiers in Education Conference (FIE), 2014 (IN PRESS), Madrid, Spain, 2014.[Abstract]

An Intelligent Tutoring System (ITS) supplements traditional learning methods and is used for personalized learning purposes that range from exploring simple examples to understanding intricate problems. The Bayesian Knowledge Tracing (BKT) model is an established method for student modeling. A recent enhancement to the BKT model is the BKT-PPS (Prior Per Student) which introduces a prior learnt for each student. Although this method demonstrates improved prediction results compared to the others, there are several aspects that limit its usefulness; (a) for a student, the prior learning is common for all skills, however in reality, it varies for each skill (b) Different students have varying learning capabilities; therefore these students cannot be considered as a homogenous group. In this paper, we aim to improve the prediction of student performance using an enhanced BKT model called the PC-BKT (Personalized & Clustered) with individual priors for each student and skill, and dynamic clustering of students based on changing learning ability. We evaluate the predictions in terms of future performance within ASSISTments intelligent tutoring dataset using over 240,000 log data and show that our models increase the accuracy of student prediction in both the general and the cold start problem.

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PDF iconpredicting-students-performance-on-intelligen-tutoring-system-personalized-clustered-bkt-pc-bkt-model.pdf

2014

Dr. Shyam Diwakar, Dr. Bipin G. Nair, Sasidharakurup, H., Radhamani, R., Sujatha, G., Shekhar, A., Achuthan, K., Prof. Nedungadi, P., and Raghu Raman, “Usage and Diffusion of Biotechnology Virtual Labs for Enhancing University education in India’s Urban and Rural Areas”, E-Learning as a Socio-Cultural System: A Multidimensional Analysis, pp. 63-83, 2014.[Abstract]

Information and Communication Technology (ICT)-enabled virtual laboratories provide an online learning experience with the aid of computer-based instructional materials (animation, simulation, and remote-trigger experiments) for improving the active learning process. The project reported on in this chapter was set up in order to enhance university and college education, which is now becoming an advanced training environment for solving the geographical, social, and economic challenges faced in the interdisciplinary field of science education, especially in India. In order to study the role of biotechnology virtual laboratories in the current education system, a pedagogical survey, via workshops and online feedback, was carried out among several student and teacher groups of different Indian universities. This chapter reports how virtual labs in biotechnology can be used to improve teaching and learning experiences in an easy and understandable way with user interaction and how such tools serve to effectively reduce the problems of laboratory education especially in remote areas. The results obtained from user-feedback analysis suggest the use of virtual labs as a recommended component in blended education in large classroom scenarios for enhancing autonomous learning process and as an alternative to enhance lab education in geographically remote and economically challenged institutes.

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PDF iconusage-and-diffusion-of-biotechnology-virtual-labs-for-enhancing-university-education-in-india-s-urban-and-rural-areas.pdf

2014

Raghu Raman, Kv, Ub, V Smrithi Rekha, and Prof. Nedungadi, P., “Using WebGL to implement a glass lens in Online Labs”, in 2014 7th International Conference on Contemporary Computing, IC3 2014, 2014, pp. 50-55.[Abstract]

Online Labs are revolutionizing education by offering access to content anytime and from any place. The OLabs project has had a deep impact on learning capabilities of students by providing an integrated environment that includes videos, animations, simulations and textual content. It has also helped to substitute teachers wherever there have been gaps. OLabs offers an excellent platform for the improvement of Science, Technology, Engineering and Maths (STEM) education which has been the focus of several countries in recent times. The current content in OLabs is 2 dimensional. 2D content comes with its own limitations of low accuracy and low realism and hence moving to browser based 3D representations is important to offer an enriching experience to the learner. WebGL offers the powerful capability of rendering 2D as well as 3D content in any browser without the need to install additional applications or components. With the advent of WebGL, writing 3D applications have become simpler since most details are abstracted from the programmer. New features are added almost every week in WebGL by the community making it rich and powerful. In this paper we present our work on implementing, in 3D, a convex lens experiment in OLabs Physics using WebGL and dynamic cube mapping. We propose to extend this work to more experiments in Physics and Chemistry, demonstrate it to students and measure their learning. © 2014 IEEE.

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PDF iconusing-webgl-to-implement-a-glass-lens-in-online-labs.pdf

2014

P. Prof. Nedungadi, Harikumar, H., and Dr. Maneesha V. Ramesh, “A high performance hybrid algorithm for text classification”, in Applications of Digital Information and Web Technologies (ICADIWT), 2014 Fifth International Conference on the, 2014.[Abstract]

The high computational complexity of text classification is a significant problem with the growing surge in text data. An effective but computationally expensive classification is the k-nearest-neighbor (kNN) algorithm. Principal Component Analysis (PCA) has commonly been used as a preprocessing phase to reduce the dimensionality followed by kNN. However, though the dimensionality is reduced, the algorithm requires all the vectors in the projected space to perform the kNN. We propose a new hybrid algorithm that uses PCA &amp; kNN but performs kNN with a small set of neighbors instead of the complete data vectors in the projected space, thus reducing the computational complexity. An added advantage in our method is that we are able to get effective classification using a relatively smaller number of principal components. New text for classification is projected into the lower dimensional space and kNN is performed only with the neighbors in each axis based on the principal that vectors that are closer in the original space are closer in the projected space and also along the projected components. Our findings with the standard benchmark dataset Reuters show that the proposed model significantly outperforms kNN and the standard PCA-kNN hybrid algorithms while maintaining similar classification accuracy.

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PDF iconHigh-Performing-Feature-Selection-for-Text-Classification.pdf

2014

Raghu Raman, Vachhrajani, H., Dr. Avinash Shivdas, and Prof. Nedungadi, P., “Low cost tablets as disruptive educational innovation: modeling its diffusion within Indian K12 system”, in Innovations in Technology Conference (InnoTek), 2014 IEEE, 2014.[Abstract]

The world of today is not looking for innovations that are mere incremental but those that are disruptive. Aakash, the Low Cost Tablet (LCT) initiative by Indian govt. was launched in 2011 amidst dominance by the likes of Apple, Amazon, and Samsung etc. Single most objective of this initiative was affordable ICT learning tool for the 220+ million students. LCT like Aakash can be seen as a disruptive innovation from the as they are simple to use, cheap, low performing, targeted at low portion of mainstream market and focused on social sectors like education, health to increase access and equity. Within Rogers theory of Diffusion of Innovation, we propose a framework for innovation attributes that can significantly predict student and teacher behavior intentions and motivations towards LCT for use in classrooms. Authors investigate the innovation attributes for adoption of LCT in a social group comprising of (N=121) potential-adopter students and teachers from India. The results revealed that motivations for adopting LCT are strongly associated with innovation attributes like relative advantage, compatibility, ease of use, peer influence, perceived enjoyment and perceived usefulness. Overall, both teachers and students expressed positive attitude towards using LCT as it enhanced their digital literacy skills. Bigger question is to identify what kind of new teacher training program, models and approaches and learning environment are required for successful adoption of educational innovation like LCT. Findings contribute to the design of new pedagogical models that maximizes learning potential of LCTs for K12 education.

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PDF iconLow Cost Tablets as disruptive educational innovation- Modeling its diffusion within Indian K12 system.pdf

2014

Dr. Krishnashree Achuthan, S., F., Prof. Nedungadi, P., Raghu Raman, l., B., Dr. Sreekala C. O., and Sreelatha, K. S., “Improving Perception of Invisible Phenomena in UG Physics Education Using ICT”, in International Conference on Information and Communication Technology (IEEE Xplore), 2014.[Abstract]

Experimental learning plays paramount role in Physics education. Experimental physics requires phenomenological investigations in several cases and this includes understanding visible and invisible heuristic procedures to discern underlying concepts. This study investigates the invisible yet evident occurrences of physical phenomena that are difficult to grasp from a learner's perspective. In this work the contribution of compounded effects of using computational techniques, multimedia enhanced simulations and interactive animations to draw the learner's attention to those physically undiscernable aspects of physics experiments is presented. The study has investigated three physics experiments by engineering students (N= 42) and the methodology focused on differentiating the learning outcomes between classroom teaching, laboratory experimentation and virtual laboratories. The students were divided into two batches. Visual and conceptual understanding was quantified by assessments that included their visual and conceptual understanding. Our study not only revealed severe limitations in learning invisible phenomena based on traditional classroom methods but also empirically validated the positive impact on learning outcomes when the classroom method is combined with Virtual Labs approach.

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PDF iconimproving-perception-of-invisible-phenomena-in-ug-physics-education-using-ict.pdf

2014

Dr. Shyam Diwakar, Parasuram, H., Medini, Ca, Raghu Raman, Prof. Nedungadi, P., Wiertelak, Ed, Srivastava, Se, Dr. Krishnashree Achuthan, and Dr. Bipin G. Nair, “Complementing neurophysiology education for developing countries via cost-effective virtual labs: Case studies and classroom scenarios”, Journal of Undergraduate Neuroscience Education, vol. 12, pp. A130-A139, 2014.[Abstract]

Classroom-level neuroscience experiments vary from detailed protocols involving chemical, physiological and imaging techniques to computer-based modeling. The application of Information and Communication Technology (ICT) is revolutionizing the current laboratory scenario in terms of active learning especially for distance education cases. Virtual web-based labs are an asset to educational institutions confronting economic issues in maintaining equipment, facilities and other conditions needed for good laboratory practice. To enhance education, we developed virtual laboratories in neuroscience and explored their first-level use in (Indian) University education in the context of developing countries. Besides using interactive animations and remotely-triggered experimental devices, a detailed mathematical simulator was implemented on a web-based software platform. In this study, we focused on the perceptions of technology adoption for a virtual neurophysiology laboratory as a new pedagogy tool for complementing college laboratory experience. The study analyses the effect of virtual labs on users assessing the relationship between cognitive, social and teaching presence. Combining feedback from learners and teachers, the study suggests enhanced motivation for students and improved teaching experience for instructors. © Faculty for Undergraduate Neuroscience.

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PDF iconcomplementing-neurophysiology-education-for-developing-countries-via-cost-effective-virtual-labs-case-studies-&-classroom-scenarios.pdf

2014

Raghu Raman, Prof. Nedungadi, P., and Dr. Maneesha V. Ramesh, “Modeling diffusion of tabletop for collaborative learning using interactive science lab simulations”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8337 LNCS, pp. 333-340, 2014.[Abstract]

Within the context of Roger's Diffusion of Innovation theory we propose a pedagogical framework for attributes that can significantly affect student adoption of collaborative learning environment like multi-user, multi-touch tabletop. We investigated the learning outcomes of secondary school students in India collaboratively using OLabs on a tabletop (EG1 = 30) vs. individually using at desktops (EG2 = 92). We analyzed the nature of communication, touch and non-touch gesture actions, position around the tabletop, focus group interviews, and pre and post test scores. Using Bass model the study also accounts for the inter influence of related group of potential adopter teachers who are likely to exert positive influence on students. The results revealed that learning outcomes on tabletop are strongly associated with innovation attributes like Relative Advantage, Compatibility, Ease of Use, Perceived Enjoyment, Perceived usefulness and Teachers support. Overall students expressed much more positive attitude to adopt tabletop technology for learning vs. desktop. We find that the mean group performance gain is significant with collaboration using tabletop and significantly greater than the group using desktops. We also find that the group interactions with the tabletop area significant factor that contributes to the group's average performance gain. However, the total time spent in while using the tabletop is surprisingly not a significant factor in the performance gain. Our findings contribute to the design of new pedagogical models for science learning that maximizes the collaborative learning potential of tabletops. © 2014 Springer International Publishing Switzerland.

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PDF iconmodeling-diffusion-tabletop-collaborative-learning-using-interactive-science-lab-simulations.pdf

2014

P. Prof. Nedungadi and Raj, H., “Unsupervised word sense disambiguation for automatic essay scoring”, Smart Innovation, Systems and Technologies, vol. 27, pp. 437-443, 2014.[Abstract]

The reliability of automated essay scoring (AES) has been the subject of debate among educators. Most systems treat essays as a bag of words and evaluate them based on LSA, LDA or other means. Many also incorporate syntactic information about essays such as the number of spelling mistakes, number of words and so on. Towards this goal, a challenging problem is to correctly understand the semantics of the essay to be evaluated so as to differentiate the intended meaning of terms used in the context of a sentence. We incorporate an unsupervised word sense disambiguation (WSD) algorithm which measures similarity between sentences as a preprocessing step to our existing AES system. We evaluate the enhanced AES model with the Kaggle AES dataset of 1400 pre-scored text answers that were manually scored by two human raters. Based on kappa scores, while both models had weighted kappa scores comparable to the human raters, the model with the WSD outperformed the model without the WSD.

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PDF iconunsupervised-word-sense-disambiguation-for-automatic-essay-scoring.pdf

2014

P. Prof. Nedungadi, Jayakumar, A., and Raghu Raman, “Low cost tablet enhanced pedagogy for early grade reading: Indian context”, in IEEE Region 10 Humanitarian Technology Conference (R10-HTC), Chennai, 2014.[Abstract]

In our research we have designed pedagogy for Low Cost Tablets (LCT) to enhance early grade reading in multi-grade classrooms in rural areas of India. The use of LCT helps meet the challenge of education in areas where there is a lack of qualified tutors and shortage of computing resources. The program has been implemented with (N=38) students in tribal areas of Kerala. Reading was the most common problem with the primary children, while mathematics and reading comprehension was a major challenge for children who were in middle school. Our pilot study students were able to learn faster on their own without requiring formal training due to the ease of use and the touch based interface of LCT, and they liked the idea of repeating lessons as many times as they wished. Teachers were trained in the use of LCT for assessment and early intervention and effective ways to bring up the reading skills of the students. Our findings confirm that LCT is powerful motivator in education and has a huge potential to address the issue of school dropouts. Our proposed pedagogy for LCT and findings will be of interest to educational policy makers who are looking at LCT options such as Aakash tablets to improve literacy levels among early grade learners.

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PDF iconlow-cost-tablet-enhanced-pedagogy-for-early-grade-reading-indian-context.pdf

2014

Raghu Raman, Achuthan, K., Prof. Nedungadi, P., Dr. Shyam Diwakar, and Bose, R., “Modeling Potential-Adopter Student Acceptance”, IEEE Transactions on Education, vol. 57, pp. 235-241, 2014.[Abstract]

Virtual Labs (VLAB) is a multi-institutional Open Educational Resources (OER) initiative, exclusively focused on lab experiments for engineering education. This project envisages building a large OER repository, containing over 1650 virtual experiments mapped to the engineering curriculum. The introduction of VLAB is a paradigm shift in an educational system that is slow to change. Treating VLAB OER as an educational technology innovation, its adoption by potential-adopter engineering students (N=131) is modeled based on Roger's theory of perceived attributes. Regression and factor analysis were used to analyze the data. Results indicate that the attributes of Compatibility, Ease of Use, Relative Advantage, and Trialability significantly influence potential-adopter students' intention to adopt an innovation like VLAB. The study also observed that using OER (such as VLAB) on desktops and low-cost tablets had similar effects in student performance to using physical labs. This has interesting implications for education policy-makers who are looking to reduce the digital divide. More »»
PDF iconmodeling-potential-adopter-student-acceptance.pdf

2014

P. Prof. Nedungadi, L, J., and Raghu Raman, “Considering Misconceptions in Automatic Essay Scoring with A-TEST - Amrita Test Evaluation and Scoring Tool”, in e-Infrastructure and e-Services for Developing Countries: 5th International Conference, AFRICOMM 2013, Blantyre, Malawi, November 25-27, 2013, Revised Selected Papers, Cham: Springer International Publishing, 2014, pp. 271–281.[Abstract]

In large classrooms with limited teacher time, there is a need for automatic evaluation of text answers and real-time personalized feedback during the learning process. In this paper, we discuss Amrita Test Evaluation & Scoring Tool (A-TEST), a text evaluation and scoring tool that learns from course materials and from human-rater scored text answers and also directly from teacher input. We use latent semantic analysis (LSA) to identify the key concepts. While most AES systems use LSA to compare students’ responses with a set of ideal essays, this ignores learning the common misconceptions that students may have about a topic. A-TEST also uses LSA to learn misconceptions from the lowest scoring essays using this as a factor for scoring. ‘A-TEST’ was evaluated using two datasets of 1400 and 1800 pre-scored text answers that were manually scored by two teachers. The scoring accuracy and kappa scores between the derived ‘A-TEST’ model and the human raters were comparable to those between the human raters.

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PDF iconconsidering-misconceptions-in-automatic-essay-scoring-with-a-test-amrita-test-evaluation-scoring-tool.pdf

2014

G. K. R. Naveen and Prof. Nedungadi, P., “Query-based Multi-Document Summarization by Clustering of Documents”, in Proceedings of the 2014 International Conference on Interdisciplinary Advances in Applied Computing, 2014.[Abstract]

Information Retrieval (IR) systems such as search engines retrieve a large set of documents, images and videos in response to a user query. Computational methods such as Automatic Text Summarization (ATS) reduce this information load enabling users to find information quickly without reading the original text. The challenges to ATS include both the time complexity and the accuracy of summarization. Our proposed Information Retrieval system consists of three different phases: Retrieval phase, Clustering phase and Summarization phase. In the Clustering phase, we extend the Potential-based Hierarchical Agglomerative (PHA) clustering method to a hybrid PHA-ClusteringGain-K-Means clustering approach. Our studies using the DUC 2002 dataset show an increase in both the efficiency and accuracy of clusters when compared to both the conventional Hierarchical Agglomerative Clustering (HAC) algorithm and PHA.

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PDF iconquery-based-multi-document-summarization-by-clustering-of-documents.pdf

2014

P. Prof. Nedungadi and Haripriya, H., “Exploiting label dependency and feature similarity for multi-label classification”, in 2014 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2014.[Abstract]

Multi-label classification is an emerging research area in which an object may belong to more than one class simultaneously. Existing methods either consider feature similarity or label similarity for label set prediction. We propose a strategy to combine both k-Nearest Neighbor (kNN) algorithm and multiple regression in an efficient way for multi-label classification. kNN works well in feature space and multiple regression works well for preserving label dependent information with generated models for labels. Our classifier incorporates feature similarity in the feature space and label dependency in the label space for prediction. It has a wide range of applications in various domains such as in information retrieval, query categorization, medical diagnosis and marketing.

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PDF iconexploiting-label-dependency-and-feature-similarity-for-multi-label-classification.pdf

2013

Raghu Raman, Dr. Krishnashree Achuthan, and Prof. Nedungadi, P., “Virtual labs in engineering education: Modeling perceived critical mass of potential adopter teachers”, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 8095 LNCS, pp. 288-300, 2013.[Abstract]

Virtual labs for science experiments are a multimedia technology innovation. A possible growth pattern of the perceived critical mass for virtual labs adoption is modeled using (N=240) potential-adopter teachers based on Roger's theory of diffusion and of perceived attributes. Results indicate that perceived critical mass influences behavior intention to adopt a technology innovation like Virtual Labs and is affected by innovation characteristics like relative advantage, ease of use and compatibility. The work presented here models the potential-adopter teacher's perceptions and identifies the relative importance of specific factors that influence critical mass attainment for an innovation such as Virtual Labs.

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PDF iconvirtual-labs-engineering-education-modeling-perceived-critical-mass-of-potential-adopter-teachers.pdf

2013

Raghu Raman, Dr. Krishnashree Achuthan, Prof. Nedungadi, P., and Ramesh, M., “Modeling Diffusion of Blended Labs for Science Experiments among Undergraduate Engineering Student”, in AFRICOMM 2013, Springer Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering (LNICST), 2013.[Abstract]

While there is large body of work examining efficacy of Virtual Labs in engineering education, studies to date have lacked modeling Blended Labs (BL) – mix of Virtual Labs (VL) and Physical Labs (PL) for science experimentation at the university engineering level. Using Rogers theory of perceived attributes, this paper provides a research framework that identifies the attributes for BL adoption in a social group comprising of (N=246) potential adopter undergraduate engineering students. Using Bass model the study also accounts for the interinfluence of related group of potential adopter faculties who are likely to exert positive influence on students. The results revealed that acceptance of BL as an innovation and its learning outcomes are strongly associated with innovation attributes like Relative Advantage, Compatibility, Ease of Use, Department and Faculty support. Learning outcomes are very positive under BL when compared to PL, though within BL, ordering of PL and VL was not significant. For certain innovation attributes gender differences were significant. Overall students expressed much more positive attitude to adopt BL model for learning than using only PL.

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PDF iconmodeling-diffusion-of-blended-labs-for-science-experiments-among-undergraduate-engineering-student.pdf

2013

P. Prof. Nedungadi, Raghu Raman, and McGregor, M., “Enhanced STEM learning with Online Labs: Empirical study comparing physical labs, tablets and desktops”, in Frontiers in Education Conference, 2013 IEEE, 2013.[Abstract]

<p>India's educational challenge includes a large school going population, shortage of science teachers and lack of science labs in many schools. To counter this challenge, the Online Labs (OLabs) pedagogy is designed as a complete learning environment with tutorials, theory, procedure, animations, videos and simulations while the assessment includes conceptual, experimental, procedural and reporting skills. We discuss two separate empirical studies using OLabs to study the performance gains, student attitudes and preferences while using physical labs, desktops and tablets. The first study was at a school that compared students who learnt individually with OLabs on desktops, to students who learnt with the traditional teacher led physical labs. The second study was at a science camp and compared OLabs on desktops to OLabs that were context adapted for android tablets. There were significant differences between the physical labs and the self study mode using OLabs on desktops, but no significant differences between OLabs on desktops compared to OLabs on tablets.</p>

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PDF iconenhanced-stem-learning-with-online-labs-empirical-study-comparing-physical-labs-tablets-and-desktops.pdf

2012

Raghu Raman, Prof. Nedungadi, P., and Karmeshu, K., “Modelling diffusion of a personalized learning framework”, Educational Technology Research and Development, vol. 60, pp. 585–600, 2012.[Abstract]

<p>A new modelling approach for diffusion of personalized learning as an educational process innovation in social group comprising adopter-teachers is proposed. An empirical analysis regarding the perception of 261 adopter-teachers from 18 schools in India about a particular personalized learning framework has been made. Based on this analysis, teacher training (TT) has been identified as one of the dominant factor which can significantly influence decision by teachers to adopt the educational innovation. Different situations corresponding to fixed and time dependent dynamic carrying capacity of potential adopter-teachers at any time have been developed. New generalized models capturing the growth dynamics of the innovation diffusion process in conjunction with the evolutionary carrying capacity of potential adopters are investigated. The coupled dynamics allows forecasting the likelihood of success or failure of new educational innovation in a given context. Different scenarios for TT are considered based on—constant growth rate model; proportional growth rate model; stratified growth rate model. The proposed modelling framework would be of great interest to education policy makers as it has the potential to predict the likelihood of success or failure of new educational innovation.</p>

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PDF iconmodelling-diffusion-of-a-personalized-learning-framework.pdf

2012

P. Prof. Nedungadi and Raghu Raman, “A new approach to personalization: Integrating e-learning and m-learning”, Educational Technology Research and Development, vol. 60, pp. 659-678, 2012.[Abstract]

Most personalized learning systems are designed for either personal computers (e-learning) or mobile devices (m-learning). Our research has resulted in a cloud-based adaptive learning system that incorporates mobile devices into a classroom setting. This system is fully integrated into the formative assessment process and, most importantly, coexists with the present e-learning environment. Unlike many mobile learning systems, this system provides teachers with real-time feedback about individual and group learners. Its scalable and extendable architectural framework includes the server-side pedagogical recommendation of content adaptation based on the users' knowledge-levels and preferences. Content is also automatically adapted to the end device that is being used. This context-aware delivery allows users to switch between e-learning and m-learning, and between devices, without any loss in personalized content. Our work builds on a web-based Adaptive Learning and Assessment System (ALAS) that is built on the Knowledge Space Theory model. At present, this system is used at school computer labs and our goal was to widen this user-base by enhancing this system to support personalized learning on mobile devices. This study describes our process of developing this technology, and contains an empirical analysis of students' performance, perceptions, and achievements when using ALAS on both personal computers and mobile devices. © 2012 Association for Educational Communications and Technology.

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PDF icona-new-approach-to-personalization-integrating-elearning-&-mlearning.pdf

2012

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, Prof. Nedungadi, P., and Dr. Bipin G. Nair, “Biotechnology Virtual Labs: Facilitating Laboratory Access Anytime-Anywhere for Classroom Education”, Innovations in Biotechnology Edited by Dr. Eddy C. Agbo, 2012.[Abstract]

<p>Biotechnology is becoming more popular and well identified as a mainline industry.Students have shown greater interest in learning the techniques. As a discipline, biotechnology has led to new advancements in many areas. Criminal investigation has changed dramatically thanks to DNA fingerprinting. Significant advances in forensic medicine, anthropology and wildlife management have been noticed in the last few years. Biotechnology has brought out hundreds of medical diagnostic tests that keep the blood safe from infectious diseases such as HIV and also aid detection of other conditions early enough to be successfully treated.</p>

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PDF iconbiotechnology-virtual-labs-facilitating-laboratory-access-anytime-anywhere-for-classroom-education.pdf

2011

Dr. Krishnashree Achuthan, K.S. Sreelatha, S. Surendran, Dr. Shyam Diwakar, Prof. Nedungadi, P., S. Humphreys, Dr. Sreekala C. O., Dr. Zeena S. Pillai, Raghu Raman, A. Deepthi, Rathish Gangadharan, Dr. Saritha A., Jyothi Ranganatha, Sreedha Sambhudevan, and Suma Mahesh, “The VALUE @ Amrita Virtual Labs Project: Using Web Technology to Provide Virtual Laboratory Access to Students”, in Global Humanitarian Technology Conference (GHTC), 2011 IEEE, 2011, pp. 117-121.[Abstract]

In response to the Indian Ministry of Human Resource Development (MHRD) National Mission on Education through Information and Communication Technology (NME-ICT) Initiative, the Virtual and Accessible Laboratories Universalizing Education (VALUE @ Amrita) Virtual Labs Project was initiated to provide laboratory-learning experiences to college and university students across India who may not have access to adequate laboratory facilities or equipment. These virtual laboratories require only a broadband Internet connection and standard web browser. Amrita Vishwa Vidyapeetham University is part of a consortium of twelve institutions building over two hundred virtual labs covering nine key disciplines in science and engineering. This National Mission project hopes to reach out to India's millions of engineering and science students at both undergraduate and postgraduate levels. The Virtual Labs Project is providing virtual laboratory experiments that directly support the All India Council for Technical Education (AICTE) and the University Grants Commission (UGC) model curricula for engineering and sciences undergraduate and postgraduate programs.

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PDF iconthe-value-amrita-virtual-lab-project-using-web-technology-to-provide-virtual-laboratory-access-to-students.pdf

2011

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, Prof. Nedungadi, P., and Dr. Bipin G. Nair, “Enhanced facilitation of biotechnology education in developing nations via virtual labs: analysis, implementation and case-studies”, International Journal of Computer Theory and Engineering, vol. 3, pp. 1–8, 2011.[Abstract]

Methods for educating students in biotechnology require intensive training in laboratory procedures. Laboratory procedures cost Universities in terms of equipment and experienced guidance which often come short in many developing countries. Universities need revitalizing approach and well-adapted curriculum especially in terms of laboratory practice. For enhanced education at the level of University-level laboratory courses such as those in biology or biotechnology, one of the key elements is the need to allow the student to familiarize laboratory techniques in par with regular theory. The Sakshat Amrita virtual biotechnology lab project focusing on virtualizing wet-lab techniques and integrating the learning experience has added a new dimension to the regular teaching courses at the University. Establishing virtual labs requires both domain knowledge and virtualizing skills via programming, animation and device-based feedback. This paper reports a cost-effective process used in virtualizing real biotechnology labs for education at Universities. The major challenge in setting up an effective knowledge dissemination for laboratory courses was not only the scientific approach of biotechnology, but included the virtualization aspects such as usage/design scalability, deliverability efficiency, network connectivity issues, security and speed of adaptability to incorporate and update changes into existing experiments. This paper also discusses an issue-specific case-study of a functional virtual lab in biotechnology and its many issues and challenges.

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PDF iconenhanced-facilitation-of-biotechnology-education-in-developing-nations-via-virtual-labs-analysis-implementation -and-case-studies.pdf

2011

Raghu Raman, Prof. Nedungadi, P., Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Integrating Collaboration and Accessibility for Deploying Virtual Labs using VLCAP”, International Transaction Journal of Engineering, Management, & Applied Sciences & Technologies , 2011.[Abstract]

The Virtual Labs Collaboration and Accessibility Platform (VLCAP) provides tools to further India’s National Mission project: the building of over 150 Virtual Labs (VL) for over 1450 multi-disciplinary undergraduate- and postgraduate-level experiments. VLCAP optimizes VL development and deployment costs and ensures a rich, consistent learning experience. Its multi-tier, scalable architecture allows VL builders to focus on their experiments. Its modules (VL workbench, collaborative content management, repositories) have axiomatically-designed interfaces that bring speed and efficiency to design. Its integration of user-management tasks (single sign-on, role-based access control, etc.) enhances flexibility without compromising security. The key accomplishments include its application of simulation VL and its provision of easily usable authoring tools, pre-configured templates, and management and assessment modules for instructors. VLCAP’s support of multiple deployment models, including the cloud, hosted, and mixed models, ensures scalable and reliable usage in hosted environments, and secure access for learners in remote locations.

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PDF iconintegrating-collaboration-and-accessibility-for-deploying-virtual-labs-using-vlcap.pdf

2011

P. Prof. Nedungadi and Raman, R., “Computer Assessment of Practical Skills (CAPS) using Scaffolding Methodology as Enabler of Learning”, in in press,IAJC-ASEE Joint International Conference on Engineering and Technology, Hartford, USA, 2011.

2011

P. Prof. Nedungadi and Raghu Raman, “Learning-Enabled Computer Assessment of Science Labs with Scaffolds Methodology”, The Technology Interface International Journal | , vol. Volume 11, Number 2 , no. Fall/Winter 2011, 2011.[Abstract]

The crucial role of hands-on science experiments in the school science curriculum is universally accepted. However, a formal assessment of practical skills is lacking, with most schools employing traditional theory-based or multiplechoice questions (MCQs) to evaluate students. In this paper, the authors present a framework for learning-enabled assessment of practical skills, which gives due consideration to both the structure of the practical assignments and the feedback that promotes learning. This approach opens up many new possibilities that require constructivist learning and higher-order thinking skills. Judgment of skills based on performance reports may decrease students’ confidence, whereas scaffolds used during the assessment process can improve students’ proficiency. The design of various online scaffolds—used during assessment that help students focus and redirect their efforts to the appropriate task needed for mastery of a skill—are discussed here. Early studies have shown that students prefer these types of assessment to more traditional ones, where intervention includes appropriate hands-on simulation or interactive animation or a given concept.

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PDF iconlearning-enabled-computer-assessment-of-science-labs-with-scaffolds-methodology.pdf

2011

P. Prof. Nedungadi, Raman, R., Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Collaborative & Accessibility Platform for Distributed Virtual Labs”, in in press, IAJC-ASEE Joint International Conference on Engineering and Technology, Hartford, USA, 2011.

2011

R. Raman and Prof. Nedungadi, P., “Transitioning to ICT Enabled Continuous and Comprehensive evaluation – Reducing teacher workload”, in in press, 3rd International Conference on Machine Learning and Computing", Singapore, 2011.

2011

P. Prof. Nedungadi, Raghu Raman, Dr. Krishnashree Achuthan, and Dr. Shyam Diwakar, “Virtual Labs Collaborative & Accessibility Platform (VLCAP)”, in Proceedings of The 2011 IAJC-ASEE International Conference , 2011.[Abstract]

India has embarked on a National Mission project to build over 150 Virtual Labs (VL) targeting over 1450 experiments mapped to the under graduate and postgraduate curriculum. Due to the lack of user centric tools and mechanisms for VL authors, it became crucial to architect a Virtual Labs Collaborative and Accessibility Platform (VLCAP) for use by the large scientific community building multi-disciplinary VL.With multi-tier, scalable architecture at its core, the technology platform allows VL builders to focus on particular logic of their experiments. The axiomatic design of the user interfaces built into the various modules including VL workbench, collaborative content management, repositories and so on assists in functional use of the elements while reducing the overall development time of VL by individual users. Integration of common tasks in user management, such as single sign-on, role based access control etc. enhances flexibility without compromising on security.

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PDF iconvirtual-labs-collaborative-accessibility-platform-vlcap.pdf

2011

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, Prof. Nedungadi, P., and Dr. Bipin G. Nair, “VirtualLabs: Pervasive education & scenes from an ICT perspective”, in Proceedings of the 5TH GUIDE INTERNATIONAL CONFERENCE 2011, Rome, 2011.

2010

Raghu Raman and Prof. Nedungadi, P., “Performance improvements in schools with Adaptive Learning and Assessment”, in ICDLE 2010 - 2010 4th International Conference on Distance Learning and Education, Proceedings, San Juan, PR, 2010, pp. 10-14.[Abstract]

This paper presents Amrita Learning, a web-based, multimedia-enabled, Adaptive Assessment and Learning System for schools. Computer-based adaptive assessments aim to use an optimal and individualized assessment path to determine the knowledge level of students. The new goal for adaptive assessment is based on educational outcomes, which describe what learners must be able to do as a result of items studied. Assessment based on outcomes creates the initial roadmap for the educational model, ensuring that students are not learning items that are already mastered. Learners and instructors can accurately determine their areas of strengths and weaknesses, and use this to determine future instruction. This paper explains the underlying principles used in the initial adaptive assessment followed by evaluation that is closely interwoven with learning. An expert module continuously adjusts the content and method of presentation based on the sequence of learner's recent responses and prior knowledge. The system maintains and updates both the individual learner profile and group profiles. Amrita Learning, targeted to school students, is built upon the principles of spiral learning with mixed presentation from multiple skill areas, thus providing continuous reinforcement in all skill-areas. The proposed competency model has been pilot tested in both city and rural area schools. In the majority of cases where students used it consistently, there were quantifiable improvements in learning levels and performance in schools. Summaries of the results and recommendations are included in this paper.

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PDF iconperformance-improvements-in-schools-with-adaptive-learning-&-assessment.pdf.pdf

2010

Raghu Raman and Prof. Nedungadi, P., “Adaptive learning methodologies to support reforms in Continuous formative Evaluation”, in ICEIT 2010 - 2010 International Conference on Educational and Information Technology, Proceedings, Chongqing, 2010, vol. 2, pp. V2429-V2433.[Abstract]

This paper presents the extensions of Amrita Learning, a web-based, multimedia-enabled, Adaptive Assessment and Learning System for schools to facilitate Continuous and Comprehensive Evaluation (CCE). Continuous Evaluation refers to the formative assessment from the beginning of instruction and periodically during instruction and is closely interwoven with learning. Amrita Learning's CCE extension supports adaptive assessments directly mapped to CBSE curriculum, monitors proper implementation of CCE and automates, enforces, and gathers usage and performance statistics. Being an adaptive system, it already supports self-paced learning, constructivist, mixed presentation, mastery, and spiral learning. The proposed competency model has been developed and is being pilot tested at schools in India. Initial results of the study are discussed in this paper. © 2010 IEEE.

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PDF iconadaptive-learning-methodologies-support-reforms-continuous-formative-evaluation.pdf

2010

P. Prof. Nedungadi and Raghu Raman, “Effectiveness of adaptive learning with interactive animations and simulations”, in ICACTE 2010 - 2010 3rd International Conference on Advanced Computer Theory and Engineering, Proceedings, Chengdu, 2010, vol. 6, pp. V640-V644.[Abstract]

We present the adaptive simulations of Amrita Learning, a web-based, interactive eLearning program that aims to create a realistic mathematics and science laboratory environment for school students to study equipments, perform simulation experiments interactively, measure or analyze results, and understand their application, It teaches abstract concepts, such as flow of electrons and magnetic fields, using highly sophisticated and interactive simulations. The adaptive simulations follow the time tested principles of Amrita Learning, a previously discussed adaptive learning system, including adaptive sequencing, presentation and feedback. This novel system enables students to work at their own pace with learning level, content and presentation individualized based on a dynamically updated student profile. While individualized simulations, animations, tutorials, and assessments enrich learning experience, simultaneous access to the content by thousands of students makes the return on investment very high. Student feedback and assessments are used to compare the adaptive simulations and animations with the traditional laboratory. Results show that while the majority of the students preferred the ease of use, adaptive feedback and additional learning options of the adaptive simulations, they missed the group discussions and extra attention from the teacher at the traditional lab.

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PDF iconeffectiveness-of-adaptive-learning-with-interactive-animations-&-simulations.pdf

2010

Dr. Shyam Diwakar, Dr. Krishnashree Achuthan, and Prof. Nedungadi, P., “Biotechnology virtual labs- integrating wet-lab techniques and theoretical learning for enhanced learning at universities”, in DSDE 2010 - International Conference on Data Storage and Data Engineering, Bangalore, 2010, pp. 10-14.[Abstract]

For enhanced education at the level of University courses such as those in biology or biotechnology, one of the key elements is the need of time and expertise to allow the student to familiarize laboratory techniques in par with regular theory. The Sakshat Amrita virtual biotechnology lab project focusing on virtualizing wet-lab techniques and integrating the learning experience has added a new dimension to the regular teaching courses at the University. Establishing virtual labs requires both domain knowledge and virtualizing skills via programming, animation and device-based feedback. Challenges in the biotechnology sector in setting up a laboratory that integrates both the feel and phenomenon includes the medley of multiple techniques. This paper reports one such cost-effective process used in virtualizing a real biotechnology lab at the University-level. The major challenge in setting up an effective knowledge dissemination for laboratory courses was not only the scientific approach of biotechnology, but included the virtualization aspects such as usage/design scalability, deliverability efficiency, network connectivity issues, security and speed of adaptability to incorporate and update changes into existing experiments. This paper also discusses an issue-specific case-study of a functional virtual lab in biotechnology and its many issues and challenges. © 2010 IEEE. More »»
PDF iconbiotechnology-virtual-labs-integrating-wet-lab-techniques-and-theoretical-learning-for-enhanced-learning-at-universities.pdf

2009

P. Prof. Nedungadi and Raman, R., “Amrita Learning Web-based, multimedia-enabled, Adaptive Assessment for schools”, in eAsia, 2009.
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