Investigating student motivation in the context of a learning analytics intervention during a summer bridge program
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Learner goal orientations and differences in achievement levels need to be carefully considered in the design of any intervention, as the resulting approaches and tools can affect students' interpretations of their data and subsequent academic success.
“Furthermore, recent studies on the effectiveness of existing dashboards suggest that learner goal orientations (Lonn et al., 2015) and differences in achievement levels (Park & Jo, 2015) need to be carefully considered in the design of any intervention, as the resulting approaches and tools can affect students' interpretations of their data and subsequent academic success.”
From Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation (2020) · cites this paper as Lonn et al., 2015
Several researchers argue that showing an aggregated analysis with respect to peer performance is a good approach.
“Several researchers argue that showing an aggregated analysis with respect to peer performance is a good approach (Lonn et al., 2015).”
From Linking learning behavior analytics and learning science concepts: Designing a learning analytics dashboard for feedback to support learning regulation (2020) · cites this paper as Lonn et al., 2015
Cites
Intrinsic Motivation and Self-Determination in Human Behavior
Deci, E. L., & Ryan, R. M. (1985) · doi:10.1007/978-1-4899-2271-7 · Cited by 26,772 · see citing works
Leaving College: Rethinking the Causes and Cures of Student Attrition
Bean, J. P., & Tinto, V. (1988) · The Journal of Higher Education · doi:10.2307/1982243 · Cited by 7,408 · see citing works
Student Involvement: A Developmental Theory for Higher Education
Astin, A. W. (2014) · Routledge eBooks · doi:10.4324/9781315051888-15 · Cited by 5,246 · see citing works
A 2 × 2 achievement goal framework.
Elliot, A. J., & McGregor, H. A. (2001) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.80.3.501 · Cited by 3,953 · see citing works
Cognitive Apprenticeship: Teaching the Crafts of Reading, Writing, and Mathematics
Collins, A., Brown, J. S., & Newman, S. E. (2018) · Knowing, Learning, and Instruction · doi:10.4324/9781315044408-14 · Cited by 3,674 · see citing works
Goals: An approach to motivation and achievement.
Elliott, E. S., & Dweck, C. S. (1988) · Journal of Personality and Social Psychology · doi:10.1037//0022-3514.54.1.5 · Cited by 3,098 · see citing works
Approach and avoidance achievement goals and intrinsic motivation: A mediational analysis.
Elliot, A. J., & Harackiewicz, J. M. (1996) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.70.3.461 · Cited by 2,531 · see citing works
(2013) · Cited by 1,951 · see citing works
Goals: An approach to motivation and achievement.
Elliott, E. S., & Dweck, C. S. (1988) · Journal of Personality and Social Psychology · doi:10.1037/0022-3514.54.1.5 · Cited by 1,837 · see citing works
(2006) · US Department of Education · Cited by 1,586 · see citing works
(2005) · Jossey-Bass, An Imprint of Wiley · Cited by 1,462 · see citing works
Revision of achievement goal theory: Necessary and illuminating.
Harackiewicz, J. M., Barron, K. E., Pintrich, P. R., Elliot, A. J., & Thrash, T. M. (2002) · Journal of Educational Psychology · doi:10.1037/0022-0663.94.3.638 · Cited by 1,399 · see citing works
Cognitive Apprenticeship: Teaching the Craft of Reading, Writing and Mathematics
Collins, A., Brown, J. S., Newman, S. E., & Montclair State University (1988) · Thinking: The Journal of Philosophy for Children · doi:10.5840/thinking19888129 · Cited by 1,299 · see citing works
Preventing students from dropping out
Astin, A. W. (1975) · Bibliothèque et Archives nationales du Québec (Québec government) · Cited by 1,244 · see citing works
A Conceptual History of the Achievement Goal Construct.
Elliot, A. J. (2005) · Cited by 1,170 · see citing works
Mining LMS data to develop an “early warning system” for educators: A proof of concept
Macfadyen, L. P., & Dawson, S. (2010) · Computers & Education · doi:10.1016/j.compedu.2009.09.008 · Cited by 1,045 · see citing works
Course signals at Purdue: using learning analytics to increase student success
Arnold, K. E., & Pistilli, M. D. (2012) · Proceedings of the 2nd International Conference on Learning Analytics and Knowledge · doi:10.1145/2330601.2330666 · Cited by 987 · see citing works
Mentkowski, M., & Astin, A. W. (1992) · The Journal of Higher Education · doi:10.2307/1982058 · Cited by 959 · see citing works
Dennis, J. M., Phinney, J. S., & Chuateco, L. I. (2005) · Journal of college student development · doi:10.1353/csd.2005.0023 · Cited by 900 · see citing works
Preece, J. J., Rogers, Y., & Sharp, H. (2002) · Cited by 887 · see citing works
Socioeconomic Status and College: How SES Affects College Experiences and Outcomes
Walpole, M. (2003) · The Review of Higher Education · doi:10.1353/rhe.2003.0044 · Cited by 751 · see citing works
Mentkowski, M. (1992) · The Journal of Higher Education · doi:10.1080/00221546.1992.11778403 · Cited by 711 · see citing works
Cognitive apprenticeship : Teaching the craft of reading, writing, and mathematics
Collins, A. J. (1989) · Defense Technical Information Center (DTIC) · Cited by 692 · see citing works
Reasons for Studying: Motivational Orientations and Study Strategies
Nolen, S. B. (1988) · Cognition and Instruction · doi:10.1207/s1532690xci0504_2 · Cited by 670 · see citing works
Leaving College: Rethinking the Causes and Cures of Student Attrition.
Wagenaar, T. C., & Tinto, V. (1988) · Contemporary Sociology A Journal of Reviews · doi:10.2307/2069700 · Cited by 600 · see citing works
Classroom learning and motivation: Clarifying and expanding goal theory
Blumenfeld, P. C. (1992) · Journal of Educational Psychology · doi:10.1037/0022-0663.84.3.272 · Cited by 587 · see citing works
The role of academic and non-academic factors in improving college retention: ACT policy report
Lotkowski, V. A., Robbins, S. B., & Noeth, R. J. (2004) · PsycEXTRA Dataset · doi:10.1037/e420492008-001 · Cited by 443 · see citing works
Achievement Goals and Intrinsic Motivation: A Meta-Analytic Review
Rawsthorne, L. J., & Elliot, A. J. (1999) · Personality and Social Psychology Review · doi:10.1207/s15327957pspr0304_3 · Cited by 443 · see citing works
Tracking student behavior, persistence, and achievement in online courses
Morris, L. V., Finnegan, C., & Wu, S.-S. (2005) · The Internet and Higher Education · doi:10.1016/j.iheduc.2005.06.009 · Cited by 424 · see citing works
Clow, D. (2012) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2330601.2330636 · Cited by 407 · see citing works
Duval, E. (2011) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2090116.2090118 · Cited by 330 · see citing works
Achievement goals and intrinsic motivation: Their relation and their role in adaptive motivation
Heyman, G. D., & Dweck, C. S. (1992) · Motivation and Emotion · doi:10.1007/bf00991653 · Cited by 322 · see citing works
DESIRE TO FINISH COLLEGE: An Empirical Link Between Motivation and Persistence
Allen, D. F. (1999) · Research in Higher Education · doi:10.1023/a:1018740226006 · Cited by 320 · see citing works
(2012) · Cited by 311 · see citing works
Blikstein, P. (2013) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2460296.2460316 · Cited by 275 · see citing works
Strayhorn, T. L. (2010) · American Behavioral Scientist · doi:10.1177/0002764210381871 · Cited by 241 · see citing works
Visualizing patterns of student engagement and performance in MOOCs
Coffrin, C., Corrin, L., Barba, P. D., & Kennedy, G. E. (2014) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2567574.2567586 · Cited by 219 · see citing works
Reconstructing the First Year of College.
Tinto, V. (1996) · Planning for higher education · Cited by 174 · see citing works
Fritz, J. (2010) · The Internet and Higher Education · doi:10.1016/j.iheduc.2010.07.007 · Cited by 140 · see citing works
Barber, R. T., & Sharkey, M. (2012) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2330601.2330664 · Cited by 125 · see citing works
Cabrera, N. L., Miner, D. D., & Milem, J. F. (2013) · Research in Higher Education · doi:10.1007/s11162-013-9286-7 · Cited by 123 · see citing works
Bridge to Success: Insight Into Summer Bridge Program Students' College Transition
Walpole, M., Simmerman, H., Mack, C., Mills, J., Scales, M., & Albano, D. (2008) · Journal of The First-Year Experience & Students in Transition · doi:10.65005/154230708813694883 · Cited by 105 · see citing works
Krumm, A. E., Waddington, R. J., Teasley, S. D., & Lonn, S. (2014) · Springer eBooks · doi:10.1007/978-1-4614-3305-7_6 · Cited by 99 · see citing works
Self-citationLarusson, J. A., & White, B. (2014) · Springer eBooks · doi:10.1007/978-1-4614-3305-7 · Cited by 91 · see citing works
Inferring higher level learning information from low level data for the Khan Academy platform
Muñoz‐Merino, P. J., Ruipérez‐Valiente, J. A., & Kloos, C. D. (2013) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2460296.2460318 · Cited by 57 · see citing works
THE BENEFITS OF SUMMER BRIDGE PROGRAMS FOR UNDERREPRESENTED AND LOW‐INCOME TRANSFER STUDENTS
Ackermann, S. P. (1991) · Community Junior College Research Quarterly of Research and Practice · doi:10.1080/0361697910150209 · Cited by 57 · see citing works
Perceptions and use of an early warning system during a higher education transition program
Aguilar, S. J., Lonn, S., & Teasley, S. D. (2014) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2567574.2567625 · Cited by 55 · see citing works
Self-citationGrann, J., & Bushway, D. J. (2014) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2567574.2567622 · Cited by 55 · see citing works
The Wise Summer Bridge Program: Assessing Student Attrition, Retention, And Program Effectiveness
Newton, L. D., Fletcher, S. L., Newell, D., & Anderson-Rowland, M. R. (2020) · IEEE Lasers and Electro-Optics Society Annual Meeting (LEOS) · doi:10.18260/1-2--10034 · Cited by 50 · see citing works
The Impacts for Upward Bound: Final Report for Phase I of the National EvaluationPreprint
Myers, D., & Schirm, A. L. (1999) · RePEc: Research Papers in Economics · Cited by 49 · see citing works
Bridging the gap from knowledge to action
Lonn, S., Krumm, A. E., Waddington, R. J., & Teasley, S. D. (2012) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2330601.2330647 · Cited by 40 · see citing works
Self-citationStudents’ Personal Growth During the First Two Years of College
Terenzini, P. T., & Wright, T. M. (1987) · Review of higher education/The review of higher education · doi:10.1353/rhe.1987.0022 · Cited by 39 · see citing works
Issues, challenges, and lessons learned when scaling up a learning analytics intervention
Lonn, S., Aguilar, S. J., & Teasley, S. D. (2013) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/2460296.2460343 · Cited by 35 · see citing works
Self-citationSuzuki, A., Amrein‐Beardsley, A., & Perry, N. (2012) · Journal of The First-Year Experience & Students in Transition · doi:10.65005/154230712813694392 · Cited by 33 · see citing works
TrAVis to enhance online tutoring and learning activities
May, M., George, S., & Prévôt, P. (2011) · Interactive Technology and Smart Education · doi:10.1108/17415651111125513 · Cited by 33 · see citing works
Allen, D. F., & Bir, B. (2012) · Journal of College Student Retention Research Theory & Practice · doi:10.2190/cs.13.4.f · Cited by 33 · see citing works
Network analysis of trace data for the support of group work
Goggins, S., Galyen, K., & Laffey, J. M. (2010) · doi:10.1145/1880071.1880089 · Cited by 30 · see citing works
Evaluation of Summer Bridge Programs
Garcia, L. D., & Paz, C. C. (2009) · About Campus Enriching the Student Learning Experience · doi:10.1002/aca.299 · Cited by 29 · see citing works
Teranishi, R. T. (2013) · The Journal of Higher Education · doi:10.1080/00221546.2013.11777308 · Cited by 29 · see citing works
Summer Bridge Programs: Supporting All Students. ERIC Digest.
Kezar, A. J. (2000) · Cited by 27 · see citing works
Bottom line: Evaluation of summer bridge programs
Garcia, L. D., & Paz, C. C. (2009) · About Campus Enriching the Student Learning Experience · doi:10.1002/abc.299 · Cited by 26 · see citing works
Lessons learned: Institutional research as support for academic improvement
John, E. P. S. (2006) · New Directions for Institutional Research · doi:10.1002/ir.182 · Cited by 6 · see citing works
Flagged first, then by citations
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Sorted by citations
Aldowah, H., Al-Samarraie, H., & Fauzy, W. M. (2019) · Telematics and Informatics · doi:10.1016/j.tele.2019.01.007 · Cited by 564 · see citing works
Matcha, W., Uzir, N. A., Gašević, D., & Pardo, A. (2019) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2019.2916802 · Cited by 434 · see citing works
Visual learning analytics of educational data: A systematic literature review and research agenda
Vieira, C., Parsons, P., & Byrd, V. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.03.018 · Cited by 316 · see citing works
Sedrakyan, G., Malmberg, J., Verbert, K., Järvelä, S., & Kirschner, P. A. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2018.05.004 · Cited by 283 · see citing works
Jivet, I., Scheffel, M., Specht, M. M., & Drachsler, H. (2018) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3170358.3170421 · Cited by 290 · see citing works
The efficacy of learning analytics interventions in higher education: a systematic review.
Larrabee Sønderlund, A., Hughes, E., & Smith, J. (2019) · British Journal of Educational Technology · doi:10.1111/bjet.12720 · Cited by 265 · see citing works
Zhu, Y., Zhang, J. H., Au, W., & Yates, G. (2020) · Educational Technology Research and Development · doi:10.1007/s11423-020-09753-w · Cited by 267 · see citing works
Awareness Is Not Enough: Pitfalls of Learning Analytics Dashboards in the Educational Practice
Jivet, I., Scheffel, M., Drachsler, H., & Specht, M. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66610-5_7 · Cited by 222 · see citing works
Utilizing early engagement and machine learning to predict student outcomes
Gray, C., & Perkins, D. (2018) · Computers & Education · doi:10.1016/j.compedu.2018.12.006 · Cited by 215 · see citing works
Prediction of students’ early dropout based on their interaction logs in online learning environment
Mubarak, A. A., Cao, H., & Zhang, W. (2022) · Interactive Learning Environments · doi:10.1080/10494820.2020.1727529 · Cited by 170 · see citing works
Lu, O. H. T., Huang, J. C. H., Huang, A. Y. Q., & Yang, S. J. H. (2017) · Interactive Learning Environments · doi:10.1080/10494820.2016.1278391 · Cited by 167 · see citing works
A review of learning analytics intervention in higher education (2011–2018)
Wong, B. T. M., & Li, K. C. (2019) · Journal of Computers in Education · doi:10.1007/s40692-019-00143-7 · Cited by 156 · see citing works
LADA: A learning analytics dashboard for academic advising
Gutiérrez, F., Seipp, K., Ochoa, X., Chiluiza, K., Laet, T. D., & Verbert, K. (2020) · Computers in Human Behavior · doi:10.1016/j.chb.2018.12.004 · Cited by 132 · see citing works
Tsai, Y., Perrotta, C., & Gašević, D. (2019) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2019.1676396 · Cited by 148 · see citing works
OnTask: Delivering Data-Informed, Personalized Learning Support Actions
Pardo, A., Bartimote-Aufflick, K., Shum, S. B., Dawson, S., Gao, J. P., Gašević, D., Leichtweis, S., Liu, D., Martínez‐Maldonado, R., Mirriahi, N., et al. (2018) · Journal of Learning Analytics · doi:10.18608/jla.2018.53.15 · Cited by 140 · see citing works
Learning analytics dashboards: the past, the present and the future
Verbert, K., Ochoa, X., De Croon, R., Dourado, R. A., & De Laet, T. (2020) · Proceedings of the Tenth International Conference on Learning Analytics & Knowledge · doi:10.1145/3375462.3375504 · Cited by 129 · see citing works
From Data to Insights: A Layered Storytelling Approach for Multimodal Learning Analytics
Martinez-Maldonado, R., Echeverria, V., Fernandez Nieto, G., & Buckingham Shum, S. (2020) · Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376148 · Cited by 123 · see citing works
Ethical issues in learning analytics: a review of the field
Tzimas, D., & Demetriadis, S. (2021) · Educational Technology Research and Development · doi:10.1007/s11423-021-09977-4 · Cited by 119 · see citing works
Sedrakyan, G., Mannens, E., & Verbert, K. (2018) · Journal of Computer Languages · doi:10.1016/j.jvlc.2018.11.002 · Cited by 114 · see citing works
Aguilar, S. J., Karabenick, S. A., Teasley, S. D., & Baek, C. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.104085 · Cited by 109 · see citing works
Self-citationKew, S. N., & Tasir, Z. (2021) · Technology Knowledge and Learning · doi:10.1007/s10758-021-09541-2 · Cited by 116 · see citing works
The effectiveness of learning analytics for identifying at-risk students in higher education
Foster, E., & Siddle, R. (2019) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2019.1682118 · Cited by 92 · see citing works
Educational Theories and Learning Analytics: From Data to Knowledge
Wong, J., Baars, M., de Koning, B. B., van der Zee, T., Davis, D., Khalil, M., Houben, G., & PAAS, F. G. W. C. (2019) · Springer eBooks · doi:10.1007/978-3-319-64792-0_1 · Cited by 90 · see citing works
Elements of Success: Supporting at-risk student resilience through learning analytics
Russell, J. M., Smith, A. M., & Larsen, R. G. (2020) · Computers & Education · doi:10.1016/j.compedu.2020.103890 · Cited by 86 · see citing works
Utilizing Learning Analytics to Support Study Success
Wong, J., van der Zee, T., Davis, D., Khalil, M., PAAS, F. G. W. C., Baars, M., de Koning, B. B., & Houben, G. (2019) · Springer eBooks · doi:10.1007/978-3-319-64792-0 · Cited by 85 · see citing works
The importance of students’ motivational dispositions for designing learning analytics
Schumacher, C., & Ifenthaler, D. (2018) · Journal of Computing in Higher Education · doi:10.1007/s12528-018-9188-y · Cited by 84 · see citing works
Gašević, D., Greiff, S., & Shaffer, D. W. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107304 · Cited by 82 · see citing works
Learning Analytics: at the Nexus of Big Data, Digital Innovation, and Social Justice in Education
Aguilar, S. J. (2017) · TechTrends · doi:10.1007/s11528-017-0226-9 · Cited by 80 · see citing works
Self-citationIt's My Data! Tensions Among Stakeholders of a Learning Analytics Dashboard
Sun, K., Mhaidli, A. H., Watel, S., Brooks, C. A., & Schaub, F. (2019) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300824 · Cited by 77 · see citing works
Wang, D., & Han, H. (2021) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12502 · Cited by 55 · see citing works
Stojanov, A., & Daniel, B. K. (2023) · Education and Information Technologies · doi:10.1007/s10639-023-12033-8 · Cited by 61 · see citing works
RETRACTED: The impact of generative AI on essay revisions and student engagement
Lo, N., Wong, A., & Chan, S. (2025) · Computers and Education Open · doi:10.1016/j.caeo.2025.100249 · Cited by 78 · see citing works
RetractedFoster, C., & Francis, P. (2020) · Assessment & Evaluation in Higher Education · doi:10.1080/02602938.2019.1696945 · Cited by 55 · see citing works
Kia, F. S., Teasley, S. D., Hatala, M., Karabenick, S. A., & Kay, M. (2020) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3375462.3375472 · Cited by 56 · see citing works
Self-citationKhosravi, H., Shabaninejad, S., Bakharia, A., Sadiq, S. W., Indulska, M., & Gašević, D. (2021) · Journal of Learning Analytics · doi:10.18608/jla.2021.7279 · Cited by 52 · see citing works
Kew, S. N., & Tasir, Z. (2022) · Education and Information Technologies · doi:10.1007/s10639-022-10904-0 · Cited by 49 · see citing works
Valle, N., Antonenko, P., do Valle, D. R., Sommer, M., Huggins‐Manley, A. C., Dawson, K., Kim, D., & Baiser, B. (2021) · Educational Technology Research and Development · doi:10.1007/s11423-021-09998-z · Cited by 51 · see citing works
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van Leeuwen, A., Teasley, S. D., & Wise, A. F. (2022) · Solar eBooks · doi:10.18608/hla22.013 · Cited by 47 · see citing works
Self-citationKnobbout, J., & van der Stappen, E. (2020) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2020.2999970 · Cited by 46 · see citing works
Elfeky, A. I. M., & Elbyaly, M. Y. H. (2021) · Interactive Learning Environments · doi:10.1080/10494820.2021.1943688 · Cited by 52 · see citing works
Kew, S. N., & Tasir, Z. (2017) · International Conference on Learning and Teaching in Computing and Engineering (LaTICE) · doi:10.1109/latice.2017.18 · Cited by 43 · see citing works
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Waddington, R. J., Nam, S., Lonn, S., & Teasley, S. D. (2016) · Journal of Learning Analytics · doi:10.18608/jla.2016.33.13 · Cited by 41 · see citing works
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Mangaroska, K., Vesin, B., Kostakos, V., Brusilovsky, P. L., & Giannakos, M. N. (2021) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2021.3072159 · Cited by 40 · see citing works
Alalawi, K., Athauda, R., & Chiong, R. (2024) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-024-00429-7 · Cited by 64 · see citing works
Scheffel, M., Drachsler, H., Toisoul, C., Ternier, S., & Specht, M. M. (2017) · Lecture notes in computer science · doi:10.1007/978-3-319-66610-5_15 · Cited by 37 · see citing works
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Naranjo, D. M., Prieto, J. R. F., Moltó, G., & Calatrava, A. (2019) · Sensors · doi:10.3390/s19132952 · Cited by 33 · see citing works
Four paradigms in learning analytics: Why paradigm convergence matters
Baker, R. S., Gašević, D., & Karumbaiah, S. (2021) · Computers and Education Artificial Intelligence · doi:10.1016/j.caeai.2021.100021 · Cited by 32 · see citing works
Supporting Student Engagement Through Explorable Visual Narratives
Yousuf, B., & Conlan, O. (2017) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2017.2722416 · Cited by 31 · see citing works
Learning Analytics Lens: Improving Quality of Higher Education
Hooda, M. (2020) · International Journal of Emerging Trends in Engineering Research · doi:10.30534/ijeter/2020/24852020 · Cited by 30 · see citing works
Şahi̇n, M., & Yurdugül, H. (2019) · Smart Learning Environments · doi:10.1186/s40561-019-0100-7 · Cited by 30 · see citing works
Use of Learning Analytics Data in Health Care–Related Educational Disciplines: Systematic Review
Chan, A. K., Botelho, M. G., & Lam, O. L. (2018) · Journal of Medical Internet Research · doi:10.2196/11241 · Cited by 30 · see citing works
Gupta, R. K., Shukla, S., Rajan, A. T., & Aravind, S. (2022) · International Journal for Research Publication and Seminars · doi:10.36676/jrps.v11.i4.1489 · Cited by 29 · see citing works
Unfolding self‐regulated learning profiles of students: A longitudinal study
Esnaashari, S., Gardner, L. A., Arthanari, T. S., & Rehm, M. (2023) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12830 · Cited by 29 · see citing works
Contreras, L. E., Fuentes, H. J., & Rodríguez, J. I. (2020) · Formación universitaria · doi:10.4067/s0718-50062020000500233 · Cited by 27 · see citing works
Lai, C., Su, Y.-S., & Ding, T.-J. (2017) · Eurasia Journal of Mathematics Science and Technology Education · doi:10.12973/eurasia.2017.01058a · Cited by 26 · see citing works
Widget, Widget on the Wall, Am I Performing Well at All?
Scheffel, M., Drachsler, H., de Kraker, J., Kreijns, K., Slootmaker, A., & Specht, M. M. (2016) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2016.2622268 · Cited by 25 · see citing works
Open Learner Models Working in Symbiosis With Self-Regulating Learners: A Research Agenda
Winne, P. H. (2020) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-020-00212-4 · Cited by 30 · see citing works
(2017) · NORA - Norwegian Open Research Archives · Cited by 25 · see citing works
Early Identification of At-Risk Students Using Iterative Logistic Regression
Zhang, L., & Rangwala, H. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-93843-1_45 · Cited by 24 · see citing works
Utamachant, P., Anutariya, C., & Pongnumkul, S. (2023) · Smart Learning Environments · doi:10.1186/s40561-023-00257-7 · Cited by 23 · see citing works
Ahammed, F., & Smith, E. (2019) · Education Sciences · doi:10.3390/educsci9030245 · Cited by 21 · see citing works
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Agus, R., & Samuri, S. M. (2018) · Asian Journal of Assessment in Teaching and Learning · doi:10.37134/ajatel.vol8.4.2018 · Cited by 25 · see citing works
Aguilar, S. J. (2017) · Journal of Research on Technology in Education · doi:10.1080/15391523.2017.1401498 · Cited by 20 · see citing works
Self-citationSung, G., Guillain, L. V., & Schneider, B. (2025) · International Journal of Artificial Intelligence in Education · doi:10.1007/s40593-024-00455-5 · Cited by 24 · see citing works
Hall, M. M., Worsham, R. E., & Reavis, G. (2021) · Community College Review · doi:10.1177/0091552120982030 · Cited by 19 · see citing works
Harris, L. R., Wyatt‐Smith, C., & Adie, L. E. (2020) · Teachers and Teaching · doi:10.1080/13540602.2020.1739018 · Cited by 17 · see citing works
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Liz-Domínguez, M., Nistal, M. L., Rodríguez, M. C., & Mikic-Fonte, F. A. (2022) · IEEE Access · doi:10.1109/access.2022.3187732 · Cited by 16 · see citing works
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Wong, B. T. M., & Li, K. C. (2018) · International Symposium on Educational Technology · doi:10.1109/iset.2018.00047 · Cited by 16 · see citing works
Liu, Y., Wang, W., & Xu, E. (2025) · SAGE Open · doi:10.1177/21582440251336707 · Cited by 15 · see citing works
Tecnología y analítica del aprendizaje: una revisión a la literatura
Bravo, L. E. C., Bermúdez, G. M. T., & Molano, J. I. R. (2021) · Revista Científica · doi:10.14483/23448350.17547 · Cited by 15 · see citing works
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Teasley, S. D., Kay, M., Elkins, S., & Hammond, J. (2021) · Advances in analytics for learning and teaching · doi:10.1007/978-3-030-81222-5_9 · Cited by 15 · see citing works
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Aguilar, S. J., & Baek, C. (2019) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3303772.3303805 · Cited by 15 · see citing works
Self-citationWang, Y. (2025) · Scientific Reports · doi:10.1038/s41598-025-19159-4 · Cited by 14 · see citing works
Sedrakyan, G., Järvelä, S., & Kirschner, P. A. (2016) · Lirias · Cited by 14 · see citing works
Widget, widget as you lead, I am performing well indeed!
Scheffel, M., Drachsler, H., Kreijns, K., de Kraker, J., & Specht, M. M. (2017) · International Conference on Learning Analytics and Knowledge (LAK) · doi:10.1145/3027385.3027428 · Cited by 13 · see citing works
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Hong, N. W. W., Chew, E., & Sze-Meng, J. W. (2016) · International Conference on Control, Automation, Robotics and Vision (ICARCV) · doi:10.1109/icarcv.2016.7838707 · Cited by 12 · see citing works
Gong, L., & Liu, Y. (2019) · International Conference on Information and Education Technology (ICIET) · doi:10.1145/3323771.3323825 · Cited by 12 · see citing works
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Prasad, D., Totaram, R., & Usagawa, T. (2016) · The International Review of Research in Open and Distributed Learning · doi:10.19173/irrodl.v17i5.2541 · Cited by 11 · see citing works
Learner-facing learning analytic – Feedback and motivation: A critique
Maag, A., Withana, C. P., Budhathoki, S., Alsadoon, A., & Vo, T. H. (2021) · Learning and Motivation · doi:10.1016/j.lmot.2021.101764 · Cited by 13 · see citing works
Figueroa-Cañas, J., & Vinuesa, T. S. (2021) · Open Learning The Journal of Open Distance and e-Learning · doi:10.1080/02680513.2021.1971963 · Cited by 11 · see citing works
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Peña‐Ayala, A., Cárdenas-Robledo, L. A., & Sossa, H. (2017) · Studies in systems, decision and control · doi:10.1007/978-3-319-52977-6_3 · Cited by 11 · see citing works
Matuk, C. F., Tissenbaum, M., & Schneider, B. (2019) · International Journal of Computer-Supported Collaborative Learning · doi:10.1007/s11412-019-09310-5 · Cited by 11 · see citing works
Ezin, C. C., & Yılmaz, R. (2022) · Universal Access in the Information Society · doi:10.1007/s10209-022-00905-8 · Cited by 12 · see citing works
Supporting Learners in a Crisis Context with Smart Self-Assessment
Papamitsiou, Z., Lunde, M., Westermoen, J., & Giannakos, M. N. (2021) · Lecture Notes in Educational Technology · doi:10.1007/978-981-15-7869-4_14 · Cited by 9 · see citing works
Silvola, A., Sjoblom, A. M., Näykki, P., Gedrimiene, E., & Muukkonen, H. (2023) · Frontline Learning Research · doi:10.14786/flr.v11i2.1277 · Cited by 9 · see citing works
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Witte, K. D., & Chénier, M.-A. (2022) · Springer eBooks · doi:10.1007/978-3-031-16624-2_16 · Cited by 9 · see citing works
Linking Assessment and Learning Analytics to Support Learning Processes in Higher Education
Schumacher, C. (2019) · Springer eBooks · doi:10.1007/978-3-319-17727-4_166-1 · Cited by 9 · see citing works
Hu, Y.-H., Liao, B.-K., & Hsieh, C.-L. (2023) · Interactive Learning Environments · doi:10.1080/10494820.2023.2277741 · Cited by 7 · see citing works
Papamitsiou, Z. K., & Economides, A. A. (2020) · Journal of Computer Assisted Learning · doi:10.1111/jcal.12472 · Cited by 7 · see citing works
A Real-Time Predictive Model for Identifying Course Dropout in Online Higher Education
Bañeres, D., Rodríguez, M. E., & Guerrero‐Roldán, A. (2023) · IEEE Transactions on Learning Technologies · doi:10.1109/tlt.2023.3267275 · Cited by 12 · see citing works
Kleimola, R., López‐Pernas, S., Väisänen, S., Saqr, M., Sointu, E. T., & Hirsto, L. (2023) · Empirical research in vocational education and training · doi:10.1186/s40461-023-00150-0 · Cited by 7 · see citing works
Fostering Learners’ Performance with On-demand Metacognitive Feedback
Papamitsiou, Z. K., Economides, A. A., & Giannakos, M. N. (2019) · Lecture notes in computer science · doi:10.1007/978-3-030-29736-7_32 · Cited by 7 · see citing works
CORBU, E. C., & Edelhauser, E. (2021) · Sensors · doi:10.3390/s21237998 · Cited by 7 · see citing works
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Giannakos, M. N. (2022) · Springer briefs in educational communications and technology · doi:10.1007/978-3-031-14350-2 · Cited by 7 · see citing works
Bassen, J., Howley, I. K., Fast, E., Mitchell, J. C., & Thille, C. (2018) · ACM Conference on Learning @ Scale (L@S) · doi:10.1145/3231644.3231669 · Cited by 6 · see citing works
Yousuf, B., Staikopoulos, A., & Conlan, O. (2018) · Lecture notes in computer science · doi:10.1007/978-3-319-98572-5_11 · Cited by 6 · see citing works
Investigating the Effectiveness of Visual Learning Analytics in Active Video Watching
Mohammadhassan, N., & Mitrović, A. (2022) · Lecture notes in computer science · doi:10.1007/978-3-031-11644-5_11 · Cited by 6 · see citing works
Lopez, C. E., & Tucker, C. S. (2024) · Zone 1 Conference of the American Society for Engineering Education (ASEE Zone 1) · doi:10.18260/1-2-1153-33757 · Cited by 6 · see citing works
An Online Web-based Adaptive Tutoring System for University Exit Exam on IT Literacy
Wongwatkit, C. (2019) · International Conference on Advanced Communication Technology · doi:10.23919/icact.2019.8701994 · Cited by 6 · see citing works
From Big Data to Learning Analytics for a personalized learning experience
Dipace, A., Loperfido, F. F., & Scarinci, A. (2018) · Research on Education and Media · doi:10.1515/rem-2018-0009 · Cited by 5 · see citing works
- Authors
- Lonn, S., Aguilar, S. J., & Teasley, S. D.
- Affiliations
- University of Michigan (US)
- Corresponding author
- Lonn, Steven
- Venue
- Computers in Human Behavior
- Publisher
- Elsevier BV
- Published
- 2015-06
- Volume
- 47
- Pages
- 90-97
- ISSN
- 0747-5632 (ISSN-L)
- OpenAlex
- W1981210033
- Cited by
- 152
- References
- 63
- Citations by year
- 2026: 7 · 2025: 10 · 2024: 7 · 2023: 14 · 2022: 16 · 2021: 17 · 2020: 22 · 2019: 21 · 2018: 19 · 2017: 12 · 2016: 7
- FWCI
- 9.42
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Computers in Human Behavior (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Science Applications › Online Learning and Analytics
- Social Sciences › Education › Higher Education Research Studies
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Education, Achievement, and Giftedness
- Keywords
- student motivation, summer bridge programs, mastery orientation, academic advising, student retention, at-risk students, high-impact practices
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