A Learning Analytics Conceptual Framework for Augmented Reality-Supported Educational Case Studies

The deployment of augmented reality (AR) has attracted educators’ interest and introduced new opportunities in education. Additionally, the advancement of artificial intelligence has enabled educational researchers to apply innovative methods and techniques for the monitoring and evaluation of the teaching and learning process. The so-called learning analytics (LA) discipline emerged with the promise to revolutionize traditional instructional practices by introducing systematic and multidimensional ways to improve the effectiveness of the instructional process. However, the implementation of LA methods is usually associated with web-based platforms, which offer direct access to learners’ data with minimal effort or adjustments. On the other hand, the complex nature of immersive technologies and the diverse instructional approaches which are utilized in different scientific domains have limited the opportunities for research and development in this direction. Within these research contexts, we present a conceptual framework that describes the elements of an LA process tailored to the information that can be gathered from the use of educational applications, and further provide an indicative case study for AR-supported educational interventions. The current work contributes by elucidating and concretizing the design elements of AR-supported applications and provides researchers and designers with guidelines on how to apply instructional strategies in (augmented) real-world projects.

[1]  Stavros Valsamidis,et al.  Proposed S-Algo+ data mining algorithm for web platforms course content and usage evaluation , 2020, Soft Comput..

[2]  George Siemens,et al.  Guest Editorial - Learning and Knowledge Analytics , 2012, J. Educ. Technol. Soc..

[3]  Samuel Greiff,et al.  Exploring behavioural patterns during complex problem-solving , 2020, J. Comput. Assist. Learn..

[4]  Ronald Azuma,et al.  A Survey of Augmented Reality , 1997, Presence: Teleoperators & Virtual Environments.

[5]  Ioannis Kazanidis,et al.  Exploring the educational potential of three-dimensional multi-user virtual worlds for STEM education: A mixed-method systematic literature review , 2016, Education and Information Technologies.

[6]  Marc Conrad,et al.  The Added Value of the Hybrid Virtual Learning Approach: Using Virtual Environments in the Real Classroom , 2018 .

[7]  M. Conrad,et al.  Interaction With Educational Games in Hybrid Virtual Worlds , 2018 .

[8]  Stavros Valsamidis,et al.  Course Ranking and Automated Suggestions through Web Mining , 2010, 2010 10th IEEE International Conference on Advanced Learning Technologies.

[9]  Eunjung Oh,et al.  Retaining Disciplinary Talents as Informal Learning Outcomes in the Digital Age: An Exploratory Framework to Engage Undergraduate Students with Career Decision-Making Processes , 2016 .

[10]  P. Frensch,et al.  Definitions, traditions, and a general framework for understanding complex problem solving , 1995 .

[11]  Marc Conrad,et al.  Increasing student engagement through virtual interactions: How? , 2017, Virtual Reality.

[12]  Shih-Ching Yeh,et al.  Interactive Learning , 2022 .

[13]  Hendrik Drachsler,et al.  From signals to knowledge: A conceptual model for multimodal learning analytics , 2018, J. Comput. Assist. Learn..

[14]  Paul Lukowicz,et al.  Effects of augmented reality on learning and cognitive load in university physics laboratory courses , 2020, Comput. Hum. Behav..

[15]  Stavros Valsamidis,et al.  Mapping and Identifying Features of e-Learning Technology through Indexes and Metrics , 2017, CSEDU.

[16]  Ioannis Kazanidis,et al.  Modeling user Progress and Visualizing Feedback - The Case of ProPer , 2010, CSEDU.

[17]  P. Prinsloo,et al.  Learning Analytics , 2013 .

[18]  Lucrezia Crescenzi‐Lanna,et al.  Multimodal Learning Analytics research with young children: A systematic review , 2020, Br. J. Educ. Technol..

[19]  Patricia Santos,et al.  Learning design and learning analytics in mobile and ubiquitous learning: A systematic review , 2020, Br. J. Educ. Technol..

[20]  George Siemens,et al.  Learning Analytics , 2013 .

[21]  Doug Clow,et al.  The learning analytics cycle: closing the loop effectively , 2012, LAK.

[22]  Ioannis Kazanidis,et al.  Developing and Assessing Augmented Reality Applications for Mathematics with Trainee Instructional Media Designers: An Exploratory Study on User Experience , 2019, J. Univers. Comput. Sci..

[23]  Dennis Zielke,et al.  Design and Implementation of a Learning Analytics Toolkit for Teachers , 2012, J. Educ. Technol. Soc..

[24]  Olga Viberg,et al.  The current landscape of learning analytics in higher education , 2018, Comput. Hum. Behav..

[25]  Ramazan Yılmaz Enhancing community of inquiry and reflective thinking skills of undergraduates through using learning analytics-based process feedback , 2020, J. Comput. Assist. Learn..

[26]  Shih-Yeh Chen,et al.  Design and Evaluation of a Deep Learning Recommendation Based Augmented Reality System for Teaching Programming and Computational Thinking , 2020, IEEE Access.

[27]  Mi Jeong Kim,et al.  A framework for context immersion in mobile augmented reality , 2013 .

[28]  Nikolaos Pellas,et al.  The influence of computer self-efficacy, metacognitive self-regulation and self-esteem on student engagement in online learning programs: Evidence from the virtual world of Second Life , 2014, Comput. Hum. Behav..

[29]  Dirk T. Tempelaar,et al.  In search for the most informative data for feedback generation: Learning analytics in a data-rich context , 2015, Comput. Hum. Behav..

[30]  Rebecca Ferguson,et al.  Learning analytics: drivers, developments and challenges , 2012 .

[31]  T. Salakoski,et al.  Limits and Virtues of Educational Technology in Elementary School Mathematics , 2020 .

[32]  Carlos Delgado-Kloos,et al.  Augmented reality for STEM learning: A systematic review , 2018, Computers & Education.

[33]  M. Laakso,et al.  A Learning Analytics Theoretical Framework for STEM Education Virtual Reality Applications , 2020, Education Sciences.

[34]  Kenneth Moore,et al.  Classroom Teaching Skills , 1988 .

[35]  Filippo Sciarrone,et al.  Learning Analytics Models: A Brief Review , 2019, 2019 23rd International Conference Information Visualisation (IV).

[36]  Alejandro Peña-Ayala,et al.  Learning analytics: A glance of evolution, status, and trends according to a proposed taxonomy , 2018 .

[37]  Tassos A. Mikropoulos,et al.  Forecasting Students' Performance Using an Ensemble SSL Algorithm , 2018, TECH-EDU.

[38]  John P. Campbell,et al.  Academic Analytics: A New Tool for a New Era. , 2007 .

[39]  Doug Clow An overview of learning analytics , 2013 .

[40]  Nee Nee Chan,et al.  An exploration of students' lived experiences of using smartphones in diverse learning contexts using a hermeneutic phenomenological approach , 2015, Comput. Educ..

[41]  Filippo Sciarrone Machine Learning and Learning Analytics: Integrating Data with Learning , 2018, 2018 17th International Conference on Information Technology Based Higher Education and Training (ITHET).

[42]  Ulrik Schroeder,et al.  A reference model for learning analytics , 2012 .

[43]  Stavros Valsamidis,et al.  Homogeneity and Enrichment: Two Metrics for Web Applications Assessment , 2010 .

[44]  Michael S. C. Thomas,et al.  Annual Research Review: Educational neuroscience: progress and prospects , 2018, Journal of child psychology and psychiatry, and allied disciplines.

[45]  Patricia Averette Instructional Strategies , 2015, Motor Learning and Control for Dance.

[46]  Nikolaos Pellas,et al.  Theoretical Foundations of Virtual and Augmented Reality-Supported Learning Analytics , 2020, 2020 11th International Conference on Information, Intelligence, Systems and Applications (IISA.

[47]  Avanilde Kemczinski,et al.  A Systematic Mapping on the Learning Analytics Field and Its Analysis in the Massive Open Online Courses Context , 2015, Int. J. Distance Educ. Technol..

[48]  Maryam Tayefeh Mahmoudi,et al.  AR‐based value‐added visualization of infographic for enhancing learning performance , 2017, Comput. Appl. Eng. Educ..

[49]  Christian Gütl,et al.  Virtual laboratories for education in science, technology, and engineering: A review , 2016, Comput. Educ..

[50]  Stavros Valsamidis,et al.  Proposed framework for data mining in e-learning: The case of open e-class , 2009, IADIS AC.

[51]  Fridolin Wild,et al.  Learning Analytics in Augmented Reality : Blueprint for an AR / xAPI Framework , 2019, 2019 IEEE International Conference on Engineering, Technology and Education (TALE).

[52]  Mehmet Akif Ocak,et al.  Augmented reality in science laboratories: The effects of augmented reality on university students' laboratory skills and attitudes toward science laboratories , 2016, Comput. Hum. Behav..

[53]  Ben Daniel,et al.  Big Data and analytics in higher education: Opportunities and challenges , 2015, Br. J. Educ. Technol..

[54]  Stavros Valsamidis,et al.  An approach for LMS assessment , 2012 .

[55]  Anders Larrabee Sønderlund,et al.  The efficacy of learning analytics interventions in higher education: A systematic review , 2018, Br. J. Educ. Technol..

[56]  Mian Usman Sattar,et al.  Predicting Student Performance in Higher Educational Institutions Using Video Learning Analytics and Data Mining Techniques , 2020, Applied Sciences.

[57]  David Wells,et al.  Augmenting the learning experience in primary and secondary school education: a systematic review of recent trends in augmented reality game-based learning , 2019, Virtual Reality.

[58]  George Siemens,et al.  Where is research on massive open online courses headed? A data analysis of the MOOC research initiative , 2014 .

[59]  Demetrios G. Sampson,et al.  Teaching and Learning Analytics to Support Teacher Inquiry: A Systematic Literature Review , 2017 .

[60]  Hendrik Drachsler,et al.  Translating Learning into Numbers: A Generic Framework for Learning Analytics , 2012, J. Educ. Technol. Soc..

[61]  Chin-Chung Tsai,et al.  Affordances of Augmented Reality in Science Learning: Suggestions for Future Research , 2012, Journal of Science Education and Technology.

[62]  Jyh-Chong Liang,et al.  Current status, opportunities and challenges of augmented reality in education , 2013, Comput. Educ..

[63]  Stavros Valsamidis,et al.  A Clustering Methodology of Web Log Data for Learning Management Systems , 2012, J. Educ. Technol. Soc..

[64]  Nikolaos Pellas,et al.  A Scoping Review of Immersive Virtual Reality in STEM Education , 2020, IEEE Transactions on Learning Technologies.

[65]  Rebecca Ferguson,et al.  Social Learning Analytics , 2012, J. Educ. Technol. Soc..