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2017 | OriginalPaper | Chapter

1. Learning Analytics in Higher Education—A Literature Review

Authors : Philipp Leitner, Mohammad Khalil, Martin Ebner

Published in: Learning Analytics: Fundaments, Applications, and Trends

Publisher: Springer International Publishing

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Abstract

This chapter looks into examining research studies of the last five years and presents the state of the art of Learning Analytics (LA) in the Higher Education (HE) arena. Therefore, we used mixed-method analysis and searched through three popular libraries, including the Learning Analytics and Knowledge (LAK) conference, the SpringerLink, and the Web of Science (WOS) databases. We deeply examined a total of 101 papers during our study. Thereby, we are able to present an overview of the different techniques used by the studies and their associated projects. To gain insights into the trend direction of the different projects, we clustered the publications into their stakeholders. Finally, we tackled the limitations of those studies and discussed the most promising future lines and challenges. We believe the results of this review may assist universities to launch their own LA projects or improve existing ones.

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Literature
go back to reference Abdelnour-Nocera J, Oussena S, Burns C (2015) Human work interaction design of the smart university. In: Human work interaction design. Work analysis and interaction design methods for pervasive and smart workplaces. Springer International Publishing, pp 127–140 Abdelnour-Nocera J, Oussena S, Burns C (2015) Human work interaction design of the smart university. In: Human work interaction design. Work analysis and interaction design methods for pervasive and smart workplaces. Springer International Publishing, pp 127–140
go back to reference AbuKhousa E, Atif Y (2016) Virtual social spaces for practice and experience sharing. In: State-of-the-Art and Future Directions of Smart Learning. Springer, Singapore, pp 409–414 AbuKhousa E, Atif Y (2016) Virtual social spaces for practice and experience sharing. In: State-of-the-Art and Future Directions of Smart Learning. Springer, Singapore, pp 409–414
go back to reference Aguiar E, Chawla NV, Brockman J, Ambrose GA, Goodrich V (2014) Engagement vs performance: using electronic portfolios to predict first semester engineering student retention. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 103–112 Aguiar E, Chawla NV, Brockman J, Ambrose GA, Goodrich V (2014) Engagement vs performance: using electronic portfolios to predict first semester engineering student retention. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 103–112
go back to reference Aguilar S, Lonn S, Teasley SD (2014) Perceptions and use of an early warning system during a higher education transition program. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 113–117 Aguilar S, Lonn S, Teasley SD (2014) Perceptions and use of an early warning system during a higher education transition program. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 113–117
go back to reference Akhtar S, Warburton S, Xu W (2015) The use of an online learning and teaching system for monitoring computer aided design student participation and predicting student success. Int J Technol Des Edu, pp 1–20 Akhtar S, Warburton S, Xu W (2015) The use of an online learning and teaching system for monitoring computer aided design student participation and predicting student success. Int J Technol Des Edu, pp 1–20
go back to reference Arnold KE, Pistilli MD (2012) Course signals at Purdue: using learning analytics to increase student success. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 267–270 Arnold KE, Pistilli MD (2012) Course signals at Purdue: using learning analytics to increase student success. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 267–270
go back to reference Arnold KE, Lonn S, Pistilli MD (2014) An exercise in institutional reflection: the learning analytics readiness instrument (LARI). In: Proceedings of the fourth international conference on learning penetrating the black box of time-on-task estimation and knowledge. ACM, pp 163–167 Arnold KE, Lonn S, Pistilli MD (2014) An exercise in institutional reflection: the learning analytics readiness instrument (LARI). In: Proceedings of the fourth international conference on learning penetrating the black box of time-on-task estimation and knowledge. ACM, pp 163–167
go back to reference Asif R, Merceron A, Pathan MK (2015) Investigating performance of students: a longitudinal study. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 108–112 Asif R, Merceron A, Pathan MK (2015) Investigating performance of students: a longitudinal study. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 108–112
go back to reference Atif A, Richards D, BilginA, Marrone M (2013) Learning analytics in higher education: a summary of tools and approaches. In: 30th Australasian Society for computers in learning in tertiary education conference, Sydney Atif A, Richards D, BilginA, Marrone M (2013) Learning analytics in higher education: a summary of tools and approaches. In: 30th Australasian Society for computers in learning in tertiary education conference, Sydney
go back to reference Barber R, Sharkey M (2012) Course correction: using analytics to predict course success. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 259–262 Barber R, Sharkey M (2012) Course correction: using analytics to predict course success. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 259–262
go back to reference Best M, MacGregor D (2015) Transitioning design and technology education from physical classrooms to virtual spaces: implications for pre-service teacher education. Int J Technol Des Edu, pp 1–13 Best M, MacGregor D (2015) Transitioning design and technology education from physical classrooms to virtual spaces: implications for pre-service teacher education. Int J Technol Des Edu, pp 1–13
go back to reference Bichsel J (2012) Analytics in higher education: benefits, barriers, progress, and recommendations. EDUCAUSE Center for Applied Research Bichsel J (2012) Analytics in higher education: benefits, barriers, progress, and recommendations. EDUCAUSE Center for Applied Research
go back to reference Bramucci R, Gaston J (2012) Sherpa: increasing student success with a recommendation engine. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 82–83 Bramucci R, Gaston J (2012) Sherpa: increasing student success with a recommendation engine. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 82–83
go back to reference Cambruzzi WL, Rigo SJ, Barbosa JL (2015) Dropout prediction and reduction in distance education courses with the learning analytics multitrail approach. J UCS 21(1):23–47 Cambruzzi WL, Rigo SJ, Barbosa JL (2015) Dropout prediction and reduction in distance education courses with the learning analytics multitrail approach. J UCS 21(1):23–47
go back to reference Campbell JP, DeBlois PB, Oblinger DG (2007) Academic analytics: a new tool for a new era. EDUCAUSE Rev 42(4):40–57 Campbell JP, DeBlois PB, Oblinger DG (2007) Academic analytics: a new tool for a new era. EDUCAUSE Rev 42(4):40–57
go back to reference Casquero O, Ovelar R, Romo J, Benito M (2014) Personal learningenvironments, highereducation and learninganalytics: a study of theeffects of servicemultiplexityonundergraduatestudents’ personal networks/Entornos de aprendizaje personales, educación superior y analítica del aprendizaje: un estudio sobre los efectos de la multiplicidad de servicios en las redes personales de estudiantes universitarios. Cultura y Educación 26(4):696–738CrossRef Casquero O, Ovelar R, Romo J, Benito M (2014) Personal learningenvironments, highereducation and learninganalytics: a study of theeffects of servicemultiplexityonundergraduatestudents’ personal networks/Entornos de aprendizaje personales, educación superior y analítica del aprendizaje: un estudio sobre los efectos de la multiplicidad de servicios en las redes personales de estudiantes universitarios. Cultura y Educación 26(4):696–738CrossRef
go back to reference Casquero O, Ovelar R, Romo J, Benito M, Alberdi M (2016) Students’ personal networks in virtual and personal learning environments: a case study in higher education using learning analytics approach. Interact Learning Environ 24(1):49–67CrossRef Casquero O, Ovelar R, Romo J, Benito M, Alberdi M (2016) Students’ personal networks in virtual and personal learning environments: a case study in higher education using learning analytics approach. Interact Learning Environ 24(1):49–67CrossRef
go back to reference Clow D (2014) Data wranglers: human interpreters to help close the feedback loop. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 49–53 Clow D (2014) Data wranglers: human interpreters to help close the feedback loop. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 49–53
go back to reference Corrigan O, Smeaton AF, Glynn M, Smyth S (2015) Using educational analytics to improve test performance. In: Design for teaching and learning in a networked world. Springer International Publishing, pp 42–55 Corrigan O, Smeaton AF, Glynn M, Smyth S (2015) Using educational analytics to improve test performance. In: Design for teaching and learning in a networked world. Springer International Publishing, pp 42–55
go back to reference Delen D (2010) A comparative analysis of machine learning techniques for student retention management. Decis Support Syst 49(4):498–506CrossRef Delen D (2010) A comparative analysis of machine learning techniques for student retention management. Decis Support Syst 49(4):498–506CrossRef
go back to reference Drachsler H, Greller W (2012) The pulse of learning analytics understandings and expectations from the stakeholders. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 120–129 Drachsler H, Greller W (2012) The pulse of learning analytics understandings and expectations from the stakeholders. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 120–129
go back to reference Elbadrawy A, Studham RS, Karypis G (2015) Collaborative multi-regression models for predicting students’ performance in course activities. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 103–107 Elbadrawy A, Studham RS, Karypis G (2015) Collaborative multi-regression models for predicting students’ performance in course activities. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 103–107
go back to reference Elias T (2011) Learning analytics: definitions, processes and potential Elias T (2011) Learning analytics: definitions, processes and potential
go back to reference Ferguson R (2012) Learning analytics: drivers, developments and challenges. Int J Technol Enhanced Learning 4(5/6):304–317CrossRef Ferguson R (2012) Learning analytics: drivers, developments and challenges. Int J Technol Enhanced Learning 4(5/6):304–317CrossRef
go back to reference Ferguson R, Shum SB (2012) Social learning analytics: five approaches. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 23–33 Ferguson R, Shum SB (2012) Social learning analytics: five approaches. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 23–33
go back to reference Freitas S, Gibson D, Du Plessis C, Halloran P, Williams E, Ambrose M, Dunwell I, Arnab S (2015) Foundations of dynamic learning analytics: using university student data to increase retention. Br J Educational Technol 46(6):1175–1188CrossRef Freitas S, Gibson D, Du Plessis C, Halloran P, Williams E, Ambrose M, Dunwell I, Arnab S (2015) Foundations of dynamic learning analytics: using university student data to increase retention. Br J Educational Technol 46(6):1175–1188CrossRef
go back to reference Fritz J (2011) Classroom walls that talk: using online course activity data of successful students to raise self-awareness of underperforming peers. Internet Higher Edu 14(2):89–97CrossRef Fritz J (2011) Classroom walls that talk: using online course activity data of successful students to raise self-awareness of underperforming peers. Internet Higher Edu 14(2):89–97CrossRef
go back to reference Gasevic D, Kovanovic V, Joksimovic S, Siemens G (2014) Where is research on massive open online courses headed? A data analysis of the MOOC research initiative. Int Rev Res Open Distrib Learning, 15(5) Gasevic D, Kovanovic V, Joksimovic S, Siemens G (2014) Where is research on massive open online courses headed? A data analysis of the MOOC research initiative. Int Rev Res Open Distrib Learning, 15(5)
go back to reference Gašević D, Dawson S, Siemens G (2015) Let’s not forget: learning analytics are about learning. TechTrends 59(1):64–71CrossRef Gašević D, Dawson S, Siemens G (2015) Let’s not forget: learning analytics are about learning. TechTrends 59(1):64–71CrossRef
go back to reference Gibson D, de Freitas S (2016) Exploratory analysis in learning analytics. Technol Knowl Learning 21(1):5–19CrossRef Gibson D, de Freitas S (2016) Exploratory analysis in learning analytics. Technol Knowl Learning 21(1):5–19CrossRef
go back to reference Gibson A, Kitto K, Willis J (2014) A cognitive processing framework for learning analytics. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 212–216 Gibson A, Kitto K, Willis J (2014) A cognitive processing framework for learning analytics. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 212–216
go back to reference Grann J, Bushway D (2014) Competency map: visualizing student learning to promote student success. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 168–172 Grann J, Bushway D (2014) Competency map: visualizing student learning to promote student success. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 168–172
go back to reference Grau-Valldosera J, Minguillón J (2011) Redefining dropping out in online higher education: a case study from the UOC. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 75–80 Grau-Valldosera J, Minguillón J (2011) Redefining dropping out in online higher education: a case study from the UOC. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 75–80
go back to reference Grau-Valldosera J, Minguillón J (2014) Rethinking dropout in online higher education: The case of the UniversitatOberta de Catalunya. Int Rev Res Open Distrib Learning, 15(1) Grau-Valldosera J, Minguillón J (2014) Rethinking dropout in online higher education: The case of the UniversitatOberta de Catalunya. Int Rev Res Open Distrib Learning, 15(1)
go back to reference Greller W, Ebner M, Schön M (2014) Learning analytics: from theory to practice–data support for learning and teaching. In: Computer assisted assessment. Research into e-assessment. Springer International Publishing, pp 79–87 Greller W, Ebner M, Schön M (2014) Learning analytics: from theory to practice–data support for learning and teaching. In: Computer assisted assessment. Research into e-assessment. Springer International Publishing, pp 79–87
go back to reference Harrison S, Villano R, Lynch G, Chen G (2015) Likelihood analysis of student enrollment outcomes using learning environment variables: a case study approach. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 141–145 Harrison S, Villano R, Lynch G, Chen G (2015) Likelihood analysis of student enrollment outcomes using learning environment variables: a case study approach. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 141–145
go back to reference Hecking T, Ziebarth S, Hoppe HU (2014) Analysis of dynamic resource access patterns in a blended learning course. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 173–182 Hecking T, Ziebarth S, Hoppe HU (2014) Analysis of dynamic resource access patterns in a blended learning course. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 173–182
go back to reference Holman C, Aguilar S, Fishman B (2013) GradeCraft: what can we learn from a game-inspired learning management system? In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 260–264 Holman C, Aguilar S, Fishman B (2013) GradeCraft: what can we learn from a game-inspired learning management system? In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 260–264
go back to reference Holman C, Aguilar SJ, Levick A, Stern J, Plummer B, Fishman B (2015) Planning for success: how students use a grade prediction tool to win their classes. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 260–264 Holman C, Aguilar SJ, Levick A, Stern J, Plummer B, Fishman B (2015) Planning for success: how students use a grade prediction tool to win their classes. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 260–264
go back to reference Ifenthaler D, Widanapathirana C (2014) Development and validation of a learning analytics framework: two case studies using support vector machines. Technol Knowl Learning 19(1–2):221–240CrossRef Ifenthaler D, Widanapathirana C (2014) Development and validation of a learning analytics framework: two case studies using support vector machines. Technol Knowl Learning 19(1–2):221–240CrossRef
go back to reference Jo IH, Yu T, Lee H, Kim Y (2015) Relations between student online learning behavior and academic achievement in higher education: a learning analytics approach. In: Emerging issues in smart learning. Springer, Berlin, pp 275–287 Jo IH, Yu T, Lee H, Kim Y (2015) Relations between student online learning behavior and academic achievement in higher education: a learning analytics approach. In: Emerging issues in smart learning. Springer, Berlin, pp 275–287
go back to reference Johnson L, Adams S, Cummins M (2012) The NMC horizon report: 2012 higher education edition. The New Media Consortium, Austin Johnson L, Adams S, Cummins M (2012) The NMC horizon report: 2012 higher education edition. The New Media Consortium, Austin
go back to reference Johnson L, Adams Becker S, Cummins M, Freeman A, Ifenthaler D, Vardaxis N (2013) Technology outlook for Australian tertiary education 2013–2018: an NMC horizon project regional analysis. New Media Consortium Johnson L, Adams Becker S, Cummins M, Freeman A, Ifenthaler D, Vardaxis N (2013) Technology outlook for Australian tertiary education 2013–2018: an NMC horizon project regional analysis. New Media Consortium
go back to reference Junco R, Clem C (2015) Predicting course outcomes with digital textbook usage data. Internet High Edu 27:54–63CrossRef Junco R, Clem C (2015) Predicting course outcomes with digital textbook usage data. Internet High Edu 27:54–63CrossRef
go back to reference Khalil M, Ebner M (2015) Learning analytics: principles and constraints. In: Proceedings of world conference on educational multimedia, hypermedia and telecommunications, pp 1326–1336 Khalil M, Ebner M (2015) Learning analytics: principles and constraints. In: Proceedings of world conference on educational multimedia, hypermedia and telecommunications, pp 1326–1336
go back to reference Khalil M, Ebner M (2016a) What is learning analytics about? A survey of different methods used in 2013–2015. In: Proceedings of smart learning conference, Dubai, UAE, 7–9 Mar. HBMSU Publishing House, Dubai, pp 294–304 Khalil M, Ebner M (2016a) What is learning analytics about? A survey of different methods used in 2013–2015. In: Proceedings of smart learning conference, Dubai, UAE, 7–9 Mar. HBMSU Publishing House, Dubai, pp 294–304
go back to reference Khousa EA, Atif Y (2014) A learning analytics approach to career readiness development in higher education. In: International conference on web-based learning. Springer International Publishing, pp 133–141 Khousa EA, Atif Y (2014) A learning analytics approach to career readiness development in higher education. In: International conference on web-based learning. Springer International Publishing, pp 133–141
go back to reference Kim J, Jo IH, Park Y (2016) Effects of learning analytics dashboard: analyzing the relations among dashboard utilization, satisfaction, and learning achievement. Asia Pac Edu Rev 17(1):13–24CrossRef Kim J, Jo IH, Park Y (2016) Effects of learning analytics dashboard: analyzing the relations among dashboard utilization, satisfaction, and learning achievement. Asia Pac Edu Rev 17(1):13–24CrossRef
go back to reference Koulocheri E, Xenos M (2013) Considering formal assessment in learning analytics within a PLE: the HOU2LEARN case. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 28–32 Koulocheri E, Xenos M (2013) Considering formal assessment in learning analytics within a PLE: the HOU2LEARN case. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 28–32
go back to reference Kovanović V, Gašević D, Dawson S, Joksimović S, Baker RS, Hatala M (2015) Penetrating the black box of time-on-task estimation. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 184–193 Kovanović V, Gašević D, Dawson S, Joksimović S, Baker RS, Hatala M (2015) Penetrating the black box of time-on-task estimation. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 184–193
go back to reference Kung-Keat T, Ng J (2016) Confused, bored, excited? An emotion based approach to the design of online learning systems. In: 7th International conference on university learning and teaching (InCULT 2014) proceedings. Springer, Singapore, pp 221–233 Kung-Keat T, Ng J (2016) Confused, bored, excited? An emotion based approach to the design of online learning systems. In: 7th International conference on university learning and teaching (InCULT 2014) proceedings. Springer, Singapore, pp 221–233
go back to reference Lauría EJ, Baron JD, Devireddy M, Sundararaju V, Jayaprakash SM (2012) Mining academic data to improve college student retention: an open source perspective. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 139–142 Lauría EJ, Baron JD, Devireddy M, Sundararaju V, Jayaprakash SM (2012) Mining academic data to improve college student retention: an open source perspective. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 139–142
go back to reference Leony D, Muñoz-Merino PJ, Pardo A, Kloos CD (2013) Provision of awareness of learners’ emotions through visualizations in a computer interaction-based environment. Expert Syst Appl 40(13):5093–5100CrossRef Leony D, Muñoz-Merino PJ, Pardo A, Kloos CD (2013) Provision of awareness of learners’ emotions through visualizations in a computer interaction-based environment. Expert Syst Appl 40(13):5093–5100CrossRef
go back to reference Liñán LC, Pérez ÁAJ (2015) Educational data mining and learning analytics: differences, similarities, and time evolution. Revista de Universidad y SociedaddelConocimiento 12(3):98–112CrossRef Liñán LC, Pérez ÁAJ (2015) Educational data mining and learning analytics: differences, similarities, and time evolution. Revista de Universidad y SociedaddelConocimiento 12(3):98–112CrossRef
go back to reference Lockyer L, Dawson S (2011) Learning designs and learning analytics. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 153–156 Lockyer L, Dawson S (2011) Learning designs and learning analytics. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 153–156
go back to reference Lonn S, Krumm AE, Waddington RJ, Teasley SD (2012) Bridging the gap from knowledge to action: Putting analytics in the hands of academic advisors. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 184–18 Lonn S, Krumm AE, Waddington RJ, Teasley SD (2012) Bridging the gap from knowledge to action: Putting analytics in the hands of academic advisors. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 184–18
go back to reference Lonn S, Aguilar S, Teasley SD (2013) Issues, challenges, and lessons learned when scaling up a learning analytics intervention. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 235–239 Lonn S, Aguilar S, Teasley SD (2013) Issues, challenges, and lessons learned when scaling up a learning analytics intervention. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 235–239
go back to reference Lotsari E, Verykios VS, Panagiotakopoulos C, Kalles D (2014) A learning analytics methodology for student profiling. In: Hellenic conference on artificial intelligence. Springer International Publishing, pp 300–312 Lotsari E, Verykios VS, Panagiotakopoulos C, Kalles D (2014) A learning analytics methodology for student profiling. In: Hellenic conference on artificial intelligence. Springer International Publishing, pp 300–312
go back to reference Ma J, Han X, Yang J, Cheng J (2015) Examining the necessary condition for engagement in an online learning environment based on learning analytics approach: the role of the instructor. Internet High Edu 24:26–34CrossRef Ma J, Han X, Yang J, Cheng J (2015) Examining the necessary condition for engagement in an online learning environment based on learning analytics approach: the role of the instructor. Internet High Edu 24:26–34CrossRef
go back to reference Machi LA, McEvoy BT (2009) The literature review: six steps to success. Corwin Sage, Thousand Oaks Machi LA, McEvoy BT (2009) The literature review: six steps to success. Corwin Sage, Thousand Oaks
go back to reference Manso-Vázquez M, Llamas-Nistal M (2015) A monitoring system to ease self-regulated learning processes. IEEE RevistaIberoamericana de TecnologiasdelAprendizaje 10(2):52–59 Manso-Vázquez M, Llamas-Nistal M (2015) A monitoring system to ease self-regulated learning processes. IEEE RevistaIberoamericana de TecnologiasdelAprendizaje 10(2):52–59
go back to reference Martin F, Whitmer JC (2016) Applying learning analytics to investigate timed release in online learning. Technol Knowl Learning 21(1):59–74CrossRef Martin F, Whitmer JC (2016) Applying learning analytics to investigate timed release in online learning. Technol Knowl Learning 21(1):59–74CrossRef
go back to reference McKay T, Miller K, Tritz J (2012) What to do with actionable intelligence: E 2 coach as an intervention engine. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 88–91 McKay T, Miller K, Tritz J (2012) What to do with actionable intelligence: E 2 coach as an intervention engine. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 88–91
go back to reference Menchaca I, Guenaga M, Solabarrieta J (2015) Project-based learning: methodology and assessment learning technologies and assessment criteria. In: Design for teaching and learning in a networked world. Springer International Publishing, pp 601–604 Menchaca I, Guenaga M, Solabarrieta J (2015) Project-based learning: methodology and assessment learning technologies and assessment criteria. In: Design for teaching and learning in a networked world. Springer International Publishing, pp 601–604
go back to reference Muñoz-Merino PJ, Valiente JAR, Kloos CD (2013) Inferring higher level learning information from low level data for the Khan Academy platform. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 112–116 Muñoz-Merino PJ, Valiente JAR, Kloos CD (2013) Inferring higher level learning information from low level data for the Khan Academy platform. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 112–116
go back to reference Nam S, Lonn S, Brown T, Davis CS, Koch D (2014) Customized course advising: investigating engineering student success with incoming profiles and patterns of concurrent course enrollment. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 16–25 Nam S, Lonn S, Brown T, Davis CS, Koch D (2014) Customized course advising: investigating engineering student success with incoming profiles and patterns of concurrent course enrollment. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 16–25
go back to reference Nespereira CG, Elhariri E, El-Bendary N, Vilas AF, Redondo RPD (2016) Machine learning based classification approach for predicting students performance in blended learning. In: The 1st International conference on advanced intelligent system and informatics (AISI2015), 28–30 Nov 2015, BeniSuef, Egypt. Springer International Publishing, pp 47–56 Nespereira CG, Elhariri E, El-Bendary N, Vilas AF, Redondo RPD (2016) Machine learning based classification approach for predicting students performance in blended learning. In: The 1st International conference on advanced intelligent system and informatics (AISI2015), 28–30 Nov 2015, BeniSuef, Egypt. Springer International Publishing, pp 47–56
go back to reference Øhrstrøm P, Sandborg-Petersen U, Thorvaldsen S, Ploug T (2013) Teaching logic through web-based and gamified quizzing of formal arguments. European conference on technology enhanced learning. Springer, Berlin, pp 410–423 Øhrstrøm P, Sandborg-Petersen U, Thorvaldsen S, Ploug T (2013) Teaching logic through web-based and gamified quizzing of formal arguments. European conference on technology enhanced learning. Springer, Berlin, pp 410–423
go back to reference Palavitsinis N, Protonotarios V, Manouselis N (2011) Applying analytics for a learning portal: the organic. Edunet case study. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 140–146 Palavitsinis N, Protonotarios V, Manouselis N (2011) Applying analytics for a learning portal: the organic. Edunet case study. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 140–146
go back to reference Palmer S (2013) Modelling engineering student academic performance using academic analytics. Int J Eng Educ 29(1):132–138 Palmer S (2013) Modelling engineering student academic performance using academic analytics. Int J Eng Educ 29(1):132–138
go back to reference Pardo A, Mirriahi N, Dawson S, Zhao Y, Zhao A, Gašević D (2015) Identifying learning strategies associated with active use of video annotation software. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 255–259 Pardo A, Mirriahi N, Dawson S, Zhao Y, Zhao A, Gašević D (2015) Identifying learning strategies associated with active use of video annotation software. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 255–259
go back to reference Park Y, Yu JH, Jo IH (2016) Clustering blended learning courses by online behavior data: a case study in a Korean higher education institute. Internet High Educ 29:1–11CrossRef Park Y, Yu JH, Jo IH (2016) Clustering blended learning courses by online behavior data: a case study in a Korean higher education institute. Internet High Educ 29:1–11CrossRef
go back to reference Piety PJ, Hickey DT, Bishop MJ (2014) Educational data sciences: framing emergent practices for analytics of learning, organizations, and systems. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 193–202 Piety PJ, Hickey DT, Bishop MJ (2014) Educational data sciences: framing emergent practices for analytics of learning, organizations, and systems. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 193–202
go back to reference Pistilli MD, Willis III JE, Campbell JP (2014) Analytics through an institutional lens: definition, theory, design, and impact. In: Learning analytics. Springer New York, pp 79–102 Pistilli MD, Willis III JE, Campbell JP (2014) Analytics through an institutional lens: definition, theory, design, and impact. In: Learning analytics. Springer New York, pp 79–102
go back to reference Prinsloo P, Slade S, Galpin F (2012) Learning analytics: challenges, paradoxes and opportunities for mega open distance learning institutions. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 130–133 Prinsloo P, Slade S, Galpin F (2012) Learning analytics: challenges, paradoxes and opportunities for mega open distance learning institutions. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 130–133
go back to reference Prinsloo P, Archer E, Barnes G, Chetty Y, Van Zyl D (2015) Big (ger) data as better data in open distance learning. Int Rev Res Open Distrib Learning, 16(1) Prinsloo P, Archer E, Barnes G, Chetty Y, Van Zyl D (2015) Big (ger) data as better data in open distance learning. Int Rev Res Open Distrib Learning, 16(1)
go back to reference Ramírez-Correa P, Fuentes-Vega C (2015) Factors that affect the formation of networks for collaborative learning: an empirical study conducted at a Chilean university/Factores que afectanla formación de redes para el aprendizajecolaborativo: unestudioempíricoconducidoenunauniversidadchilena. Ingeniare: RevistaChilena de Ingenieria, 23(3), 341 Ramírez-Correa P, Fuentes-Vega C (2015) Factors that affect the formation of networks for collaborative learning: an empirical study conducted at a Chilean university/Factores que afectanla formación de redes para el aprendizajecolaborativo: unestudioempíricoconducidoenunauniversidadchilena. Ingeniare: RevistaChilena de Ingenieria, 23(3), 341
go back to reference Rogers T, Colvin C, Chiera B (2014) Modest analytics: using the index method to identify students at risk of failure. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 118–122 Rogers T, Colvin C, Chiera B (2014) Modest analytics: using the index method to identify students at risk of failure. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 118–122
go back to reference Romero C, Ventura S (2013) Data mining in education. Wiley Interdiscip Rev Data Min Knowl Discovery 3(1):12–27CrossRef Romero C, Ventura S (2013) Data mining in education. Wiley Interdiscip Rev Data Min Knowl Discovery 3(1):12–27CrossRef
go back to reference Santos JL, Govaerts S, Verbert K, Duval E (2012) Goal-oriented visualizations of activity tracking: a case study with engineering students. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 143–152 Santos JL, Govaerts S, Verbert K, Duval E (2012) Goal-oriented visualizations of activity tracking: a case study with engineering students. In: Proceedings of the 2nd international conference on learning analytics and knowledge. ACM, pp 143–152
go back to reference Santos JL, Verbert K, Govaerts S, Duval E (2013) Addressing learner issues with StepUp!: an evaluation. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 14–22 Santos JL, Verbert K, Govaerts S, Duval E (2013) Addressing learner issues with StepUp!: an evaluation. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 14–22
go back to reference Santos JL, Verbert K, Klerkx J, Duval E, Charleer S, Ternier S (2015) Tracking data in open learning environments. J Univ Comput Sci 21(7):976–996 Santos JL, Verbert K, Klerkx J, Duval E, Charleer S, Ternier S (2015) Tracking data in open learning environments. J Univ Comput Sci 21(7):976–996
go back to reference Scheffel M, Niemann K, Leony D, Pardo A, Schmitz HC, Wolpers M, Kloos CD (2012) Key action extraction for learning analytics. European conference on technology enhanced learning. Springer, Berlin, pp 320–333 Scheffel M, Niemann K, Leony D, Pardo A, Schmitz HC, Wolpers M, Kloos CD (2012) Key action extraction for learning analytics. European conference on technology enhanced learning. Springer, Berlin, pp 320–333
go back to reference Shacklock X (2016) From bricks to clicks: the potential of data and analytics in higher education. The Higher Education Commission’s (HEC) report Shacklock X (2016) From bricks to clicks: the potential of data and analytics in higher education. The Higher Education Commission’s (HEC) report
go back to reference Sharkey M (2011) Academic analytics landscape at the University of Phoenix. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 122–126 Sharkey M (2011) Academic analytics landscape at the University of Phoenix. In: Proceedings of the 1st international conference on learning analytics and knowledge. ACM, pp 122–126
go back to reference Siemens G, Long P (2011) Penetrating the fog: analytics in learning and education. EDUCAUSE Rev 46(5):30–40 Siemens G, Long P (2011) Penetrating the fog: analytics in learning and education. EDUCAUSE Rev 46(5):30–40
go back to reference Simsek D, Sándor Á, Shum SB, Ferguson R, De Liddo A, Whitelock D (2015) Correlations between automated rhetorical analysis and tutors’ grades on student essays. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 355–359 Simsek D, Sándor Á, Shum SB, Ferguson R, De Liddo A, Whitelock D (2015) Correlations between automated rhetorical analysis and tutors’ grades on student essays. In: Proceedings of the fifth international conference on learning analytics and knowledge. ACM, pp 355–359
go back to reference Sinclair J, Kalvala S (2015) Engagement measures in massive open online courses. In: International workshop on learning technology for education in cloud. Springer International Publishing, pp 3–15 Sinclair J, Kalvala S (2015) Engagement measures in massive open online courses. In: International workshop on learning technology for education in cloud. Springer International Publishing, pp 3–15
go back to reference Slade S, Prinsloo P (2013) Learning analytics ethical issues and dilemmas. Am Behav Sci 57(10):1510–1529CrossRef Slade S, Prinsloo P (2013) Learning analytics ethical issues and dilemmas. Am Behav Sci 57(10):1510–1529CrossRef
go back to reference Softic S, Taraghi B, Ebner M, De Vocht L, Mannens E, Van de Walle R (2013) Monitoring learning activities in PLE using semantic modelling of learner behaviour. Human factors in computing and informatics. Springer, Berlin, pp 74–90CrossRef Softic S, Taraghi B, Ebner M, De Vocht L, Mannens E, Van de Walle R (2013) Monitoring learning activities in PLE using semantic modelling of learner behaviour. Human factors in computing and informatics. Springer, Berlin, pp 74–90CrossRef
go back to reference Strang KD (2016) Beyond engagement analytics: which online mixed-data factors predict student learning outcomes? Education and information technologies, pp 1–21 Strang KD (2016) Beyond engagement analytics: which online mixed-data factors predict student learning outcomes? Education and information technologies, pp 1–21
go back to reference Swenson J (2014) Establishing an ethical literacy for learning analytics. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 246–250 Swenson J (2014) Establishing an ethical literacy for learning analytics. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 246–250
go back to reference Tervakari AM, Marttila J, Kailanto M, Huhtamäki J, Koro J, Silius K (2013) Developing learning analytics for TUT Circle. Open and social technologies for networked learning. Springer, Berlin, pp 101–110CrossRef Tervakari AM, Marttila J, Kailanto M, Huhtamäki J, Koro J, Silius K (2013) Developing learning analytics for TUT Circle. Open and social technologies for networked learning. Springer, Berlin, pp 101–110CrossRef
go back to reference Tseng SF, Tsao YW, Yu LC, Chan CL, Lai KR (2016) Who will pass? Analyzing learner behaviors in MOOCs. Res Pract Technol Enhanced Learning 11(1):1CrossRef Tseng SF, Tsao YW, Yu LC, Chan CL, Lai KR (2016) Who will pass? Analyzing learner behaviors in MOOCs. Res Pract Technol Enhanced Learning 11(1):1CrossRef
go back to reference Vahdat M, Oneto L, Anguita D, Funk M, Rauterberg M (2015) A learning analytics approach to correlate the academic achievements of students with interaction data from an educational simulator. In: Design for teaching and learning in a networked world. Springer International Publishing, pp 352–366 Vahdat M, Oneto L, Anguita D, Funk M, Rauterberg M (2015) A learning analytics approach to correlate the academic achievements of students with interaction data from an educational simulator. In: Design for teaching and learning in a networked world. Springer International Publishing, pp 352–366
go back to reference van Barneveld A, Arnold KE, Campbell JP (2012) Analytics in higher education: establishing a common language. EDUCAUSE Learning Initiative 1:1–11 van Barneveld A, Arnold KE, Campbell JP (2012) Analytics in higher education: establishing a common language. EDUCAUSE Learning Initiative 1:1–11
go back to reference Vozniuk A, Holzer A, Gillet D (2014) Peer assessment based on ratings in a social media course. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 133–137 Vozniuk A, Holzer A, Gillet D (2014) Peer assessment based on ratings in a social media course. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 133–137
go back to reference Westera W, Nadolski R, Hummel H (2013) Learning analytics in serious gaming: uncovering the hidden treasury of game log files. In: international conference on games and learning alliance. Springer International Publishing, pp 41–52 Westera W, Nadolski R, Hummel H (2013) Learning analytics in serious gaming: uncovering the hidden treasury of game log files. In: international conference on games and learning alliance. Springer International Publishing, pp 41–52
go back to reference Wise AF (2014) Designing pedagogical interventions to support student use of learning analytics. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 203–211 Wise AF (2014) Designing pedagogical interventions to support student use of learning analytics. In: Proceedings of the fourth international conference on learning analytics and knowledge. ACM, pp 203–211
go back to reference Wolff A, Zdrahal Z, Nikolov A, Pantucek M (2013) Improving retention: predicting at-risk students by analysing clicking behaviour in a virtual learning environment. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 145–149 Wolff A, Zdrahal Z, Nikolov A, Pantucek M (2013) Improving retention: predicting at-risk students by analysing clicking behaviour in a virtual learning environment. In: Proceedings of the third international conference on learning analytics and knowledge. ACM, pp 145–149
go back to reference Wu IC, Chen WS (2013) Evaluating the practices in the e-learning platform from the perspective of knowledge management. Open and social technologies for networked learning. Springer, Berlin, pp 81–90CrossRef Wu IC, Chen WS (2013) Evaluating the practices in the e-learning platform from the perspective of knowledge management. Open and social technologies for networked learning. Springer, Berlin, pp 81–90CrossRef
go back to reference Yasmin D (2013) Application of the classification tree model in predicting learner dropout behaviour in open and distance learning. Dis Educ 34(2):218–231CrossRef Yasmin D (2013) Application of the classification tree model in predicting learner dropout behaviour in open and distance learning. Dis Educ 34(2):218–231CrossRef
Metadata
Title
Learning Analytics in Higher Education—A Literature Review
Authors
Philipp Leitner
Mohammad Khalil
Martin Ebner
Copyright Year
2017
DOI
https://doi.org/10.1007/978-3-319-52977-6_1

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