Educational data mining and learning analytics: An updated survey

This survey is an updated and improved version of the previous one published in 2013 in this journal with the title “data mining in education”. It reviews in a comprehensible and very general way how Educational Data Mining and Learning Analytics have been applied over educational data. In the last decade, this research area has evolved enormously and a wide range of related terms are now used in the bibliography such as Academic Analytics, Institutional Analytics, Teaching Analytics, Data‐Driven Education, Data‐Driven Decision‐Making in Education, Big Data in Education, and Educational Data Science. This paper provides the current state of the art by reviewing the main publications, the key milestones, the knowledge discovery cycle, the main educational environments, the specific tools, the free available datasets, the most used methods, the main objectives, and the future trends in this research area.

[1]  Cristóbal Romero,et al.  A survey on educational process mining , 2018, WIREs Data Mining Knowl. Discov..

[2]  RomeroCristobal,et al.  Data mining in education , 2013 .

[3]  Sebastián Ventura,et al.  Educational data science in massive open online courses , 2016, WIREs Data Mining Knowl. Discov..

[4]  Sebastián Ventura,et al.  Educational Data Mining: A Review of the State of the Art , 2010, IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews).

[5]  Una-May O'Reilly,et al.  Transfer Learning using Representation Learning in Massive Open Online Courses , 2019, LAK.

[6]  Mykola Pechenizkiy,et al.  Handbook of Educational Data Mining , 2010 .

[7]  Osmar R. Zaïane,et al.  Educational data mining applications and tasks: A survey of the last 10 years , 2017, Education and Information Technologies.

[8]  Laurence T. Yang,et al.  A survey on data fusion in internet of things: Towards secure and privacy-preserving fusion , 2019, Inf. Fusion.

[9]  P. Newton,et al.  When robots teach : towards a code of practice. , 2019 .

[10]  Isabel Hilliger,et al.  Evaluating Usage of an Analytics Tool to Support Continuous Curriculum Improvement , 2019, EC-TEL.

[11]  George Siemens,et al.  Learning analytics and educational data mining: towards communication and collaboration , 2012, LAK.

[12]  Sebastián Ventura,et al.  Educational data mining: A survey from 1995 to 2005 , 2007, Expert Syst. Appl..

[13]  George Siemens,et al.  Current state and future trends: a citation network analysis of the learning analytics field , 2014, LAK.

[14]  Sebastián Ventura,et al.  A Survey on Pre-Processing Educational Data , 2014 .

[15]  Rebecca Ferguson,et al.  Guest Editorial: Ethics and Privacy in Learning Analytics , 2016, J. Learn. Anal..

[16]  George Siemens,et al.  Ethical and privacy principles for learning analytics , 2014, Br. J. Educ. Technol..

[17]  Neil T. Heffernan,et al.  Machine-Learned or Expert-Engineered Features? Exploring Feature Engineering Methods in Detectors of Student Behavior and Affect , 2019, EDM.

[18]  George Siemens,et al.  Increasing the Impact of Learning Analytics , 2019, LAK.

[19]  Iván Martínez-Ortiz,et al.  Applications of data science to game learning analytics data: A systematic literature review , 2019, Comput. Educ..

[20]  Evandro Costa,et al.  Text mining in education , 2019, WIREs Data Mining Knowl. Discov..

[21]  Cristóbal Romero,et al.  A holographic mobile-based application for practicing pronunciation of basic English vocabulary for Spanish speaking children , 2019, Int. J. Hum. Comput. Stud..

[22]  Saurabh Pal,et al.  Mining Educational Data to Analyze Students' Performance , 2012, ArXiv.

[23]  I. Arroyo,et al.  Bayesian networks and linear regression models of students’ goals, moods, and emotions , 2010 .

[24]  Ryan S. Baker,et al.  Educational Data Mining and Learning Analytics , 2014 .

[25]  Michail N. Giannakos,et al.  Multimodal data as a means to understand the learning experience , 2019, Int. J. Inf. Manag..

[26]  Kenneth R. Koedinger,et al.  A Data Repository for the EDM Community: The PSLC DataShop , 2010 .

[27]  Jack Mostow,et al.  Some useful tactics to modify, map and mine data from intelligent tutors , 2006, Natural Language Engineering.

[28]  Stevens Dormezil,et al.  Differentiating between Educational Data Mining and Learning Analytics: A Bibliometric Approach , 2019, EDM.

[29]  Martin Ebner,et al.  Learning Analytics Challenges to Overcome in Higher Education Institutions , 2019, Utilizing Learning Analytics to Support Study Success.

[30]  Carolyn Penstein Rosé,et al.  Explanatory learner models: Why machine learning (alone) is not the answer , 2019, Br. J. Educ. Technol..

[31]  Gregory Taylor,et al.  Current and future , 1998 .

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

[33]  Isaac Seoane,et al.  Data mining in foreign language learning , 2018, WIREs Data Mining Knowl. Discov..

[34]  Ángel Alejandro Juan Pérez,et al.  Educational Data Mining and Learning Analytics: differences, similarities, and time evolution , 2015, International Journal of Educational Technology in Higher Education.

[35]  Ryan S. Baker,et al.  Challenges for the Future of Educational Data Mining: The Baker Learning Analytics Prizes , 2019 .

[36]  Marie Bienkowski,et al.  Enhancing Teaching and Learning Through Educational Data Mining and Learning Analytics: An Issue Brief , 2012 .

[37]  George Siemens,et al.  Penetrating the fog: analytics in learning and education , 2014 .

[38]  Xavier Ochoa,et al.  Current and future multimodal learning analytics data challenges , 2017, LAK.

[39]  Dragan Gasevic,et al.  Handbook of Learning Analytics , 2017 .

[40]  Dragan Gasevic,et al.  Using learning analytics to scale the provision of personalised feedback , 2019, Br. J. Educ. Technol..

[41]  Samantha Custer,et al.  Toward Data-Driven Education Systems: Insights into Using Information to Measure Results and Manage Change. , 2018 .

[42]  Sidney K. D'Mello,et al.  Emotional Learning Analytics , 2017 .

[43]  Tiffany Barnes,et al.  Exploring Induced Pedagogical Strategies Through a Markov Decision Process Framework: Lessons Learned , 2018 .

[44]  Sebastián Ventura,et al.  Data mining in course management systems: Moodle case study and tutorial , 2008, Comput. Educ..

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

[46]  Sohail Iqbal Malik,et al.  A Survey of Internet of Things (IoT) in Education: Opportunities and Challenges , 2019, Toward Social Internet of Things (SIoT): Enabling Technologies, Architectures and Applications.

[47]  Sebastián Ventura,et al.  Data mining in education , 2013, WIREs Data Mining Knowl. Discov..

[48]  Amanda Datnow,et al.  Teacher capacity for and beliefs about data-driven decision making: A literature review of international research , 2015, Journal of Educational Change.

[49]  Pierre Dillenbourg,et al.  Teaching analytics: towards automatic extraction of orchestration graphs using wearable sensors , 2016, LAK.

[50]  Dragan Gasevic,et al.  Rethinking learning analytics adoption through complexity leadership theory , 2018, LAK.

[51]  Luis E. Zárate,et al.  Causality relationship among attributes applied in an educational data set , 2019, SAC.

[52]  Ben Kei Daniel,et al.  Big Data and data science: A critical review of issues for educational research , 2019, Br. J. Educ. Technol..

[53]  Jiyi Wu,et al.  A review on sentiment discovery and analysis of educational big‐data , 2020, Wiley Interdiscip. Rev. Data Min. Knowl. Discov..

[54]  Borja Navarro-Colorado,et al.  A Systematic Review of Deep Learning Approaches to Educational Data Mining , 2019, Complex..

[55]  María Jesús Rodríguez-Triana,et al.  Orchestrating learning analytics (OrLA): Supporting inter-stakeholder communication about adoption of learning analytics at the classroom level , 2019, Australasian Journal of Educational Technology.

[56]  Carlos Delgado Kloos,et al.  Design of a Conversational Agent as an Educational Tool , 2018, 2018 Learning With MOOCS (LWMOOCS).

[57]  J. D. Leonard,et al.  Interpretable Multiview Early Warning System Adapted to Underrepresented Student Populations , 2019, IEEE Transactions on Learning Technologies.

[58]  Matthew D. Pistilli,et al.  Course signals at Purdue: using learning analytics to increase student success , 2012, LAK.

[59]  Miguel Ángel Conde González,et al.  Predicting teamwork group assessment using log data-based learning analytics , 2018, Comput. Hum. Behav..

[60]  Fred Paas,et al.  Educational Theories and Learning Analytics: From Data to Knowledge , 2019, Utilizing Learning Analytics to Support Study Success.

[61]  Ben Williamson,et al.  Brain Data: Scanning, Scraping and Sculpting the Plastic Learning Brain Through Neurotechnology , 2018, Postdigital Science and Education.

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

[63]  Khaled M. Hammouda,et al.  Data Mining in E-Learning , 2007 .

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

[65]  Ryan S. Baker,et al.  The State of Educational Data Mining in 2009: A Review and Future Visions. , 2009, EDM 2009.