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Esomonu, Nkechi Patricia-Mary; Esomonu, Martins Ndibem; Eleje, Lydia Ijeoma – International Journal of Evaluation and Research in Education, 2020
As a result of increasing complexity of assessing all aspects of human behaviours, a lot of data are generated on individual learner and from teachers and the system. What qualifies as big data in assessment in Nigeria? This research identifies the sources of assessment big data in Nigeria, investigates how the big data are generated and…
Descriptors: Foreign Countries, Expertise, Learning Analytics, Student Evaluation
Zotou, Maria; Tambouris, Efthimios; Tarabanis, Konstantinos – Educational Technology Research and Development, 2020
Problem based learning (PBL) supports the development of transversal skills and could underpin the training of a workforce competent to withstand the constant generation of new information. However, the application of PBL is still facing challenges, as educators are usually unsure how to structure student-centred courses, how to monitor students'…
Descriptors: Problem Based Learning, Data Use, Learning Analytics, Skill Development
Algayres, Muriel; Triantafyllou, Evangelia – Electronic Journal of e-Learning, 2020
The Flipped Classroom (FC) is an instruction method, where the traditional lecture and homework sessions are inverted. Online material is given to students in order to gain necessary knowledge before class, while class time is devoted to application of this knowledge and reflection. The hypothesis is that there could be deep and creative…
Descriptors: Learning Analytics, Flipped Classroom, Literature Reviews, Best Practices
Gedrimiene, Egle; Silvola, Anni; Pursiainen, Jouni; Rusanen, Jarmo; Muukkonen, Hanni – Scandinavian Journal of Educational Research, 2020
Vocational education and training (VET) remain overlooked in learning analytics (LA) research. This systematic literature review, using four databases and other sources, was carried out by analyzing selected 60 articles (2012-2017) to study the levels and stages of education that the reviewed LA literature examined. The review indicated that most…
Descriptors: Learning Analytics, Educational Technology, Educational Research, Ethics
Epler-Ruths, Colleen M.; McDonald, Scott; Pallant, Amy; Lee, Hee-Sun – Cognitive Research: Principles and Implications, 2020
This article represents the findings from the qualitative portion of a mixed methods study that investigated the impact of middle school students' spatial skills on their plate tectonics learning while using a computer visualization. Higher spatial skills have been linked to higher STEM achievement, while use of computer visualizations has mixed…
Descriptors: Spatial Ability, Middle School Students, Plate Tectonics, STEM Education
Li, Jessica; Wong, Seohyun Claire; Yang, Xue; Bell, Allison – Educational Technology Research and Development, 2020
How should learner analytics and different media be used to optimize feedback to increase students' motivation and sense of learning community in online learning programs? This study was designed to examine the usage of feedback delivery methods (text only, video only, or both) and learner analytics (individual vs. class average) to answer the…
Descriptors: Learning Analytics, Feedback (Response), Student Participation, Electronic Learning
Cirillo, Michelle; Hummer, Jenifer – North American Chapter of the International Group for the Psychology of Mathematics Education, 2020
Twenty students who earned A or B course-grades in the proof unit(s) of a secondary course that addressed proof in geometry were asked to work on two proof tasks while sharing their thinking aloud and using smartpens. Students were classified into two categories: those who were successful with both proofs and those who were unsuccessful with both…
Descriptors: Secondary School Students, Secondary School Mathematics, Mathematical Logic, Mathematics Skills
Sahin, Muhittin; Ifenthaler, Dirk – International Association for Development of the Information Society, 2020
A major criticism brought to digital learning environments was that the individual learning activities cannot be monitored consistently. However, recent advancements of educational data mining and learning analytics allow a precise tracking of learner activities. Previous studies focused on learners' navigation profiles, academic achievements, or…
Descriptors: Gender Differences, Interaction, Preferences, Undergraduate Students
Azevedo, Jose Manuel; Oliveira, Ema P.; Beites, Patrícia Damas – International Journal of Information and Learning Technology, 2019
Purpose: The purpose of this paper is to find appropriate forms of analysis of multiple-choice questions (MCQ) to obtain an assessment method, as fair as possible, for the students. The authors intend to ascertain if it is possible to control the quality of the MCQ contained in a bank of questions, implemented in Moodle, presenting some evidence…
Descriptors: Learning Analytics, Multiple Choice Tests, Test Theory, Item Response Theory
Gasevic, Dragan; Tsai, Yi-Shan; Dawson, Shane; Pardo, Abelardo – International Journal of Information and Learning Technology, 2019
Purpose: The analysis of data collected from user interactions with educational and information technology has attracted much attention as a promising approach to advancing our understanding of the learning process. This promise motivated the emergence of the field of learning analytics and supported the education sector in moving toward…
Descriptors: Learning Analytics, Adoption (Ideas), Technology Integration, Foreign Countries
Keehn, Suzanne; Claggett, Stuart – Journal of Applied Testing Technology, 2019
The educational game industry struggles from a lack of standardization around collecting, analyzing and managing student learning data, which is potentially jeopardizing millions of dollars of investment in educational games. Investors, administrators, and educators require data to support quantitative and qualitative learning measurement in…
Descriptors: Educational Games, Game Based Learning, Data Collection, Elementary Secondary Education
Jenna Marie Dulak – ProQuest LLC, 2019
The purpose of this study is to determine what demographics and learning analytics can be used as predictors to identify at-risk students in higher education. These indicators can be used to develop policies and instructional design techniques that faculty can use to intervene with at-risk students. This quantitative study uses geographic…
Descriptors: Learning Analytics, Social Indicators, At Risk Students, Educational Policy
Kowalik, Eric – Journal of Teaching and Learning with Technology, 2022
Leveraging the campus learning management system and rapid e-learning development software such as Articulate Storyline allows educators to develop and deploy interactive tutorials for performance assessment of students' knowledge. This quick hit chronicles the development, deployment, and assessment of a suite of tutorials for information…
Descriptors: Learning Management Systems, Tutorial Programs, Web Based Instruction, Academic Libraries
Vigentini, Lorenzo; Swibel, Brad; Hasler, Garth – Journal of Learning Analytics, 2022
While Learning Analytics (LA) have gained momentum in higher education, there are still few examples of application in the school sector. Even fewer cases are reported of systematic, organizational adoption to drive the support of student learning trajectories that includes teachers, pastoral leaders, and academic managers. This paper presents one…
Descriptors: Learning Analytics, Educational Improvement, Secondary School Students, Learning Management Systems
Sancenon, Vicente; Wijaya, Kharisma; Wen, Xavier Yue Shu; Utama, Diaz Adi; Ashworth, Mark; Ng, Kelvin Hongrui; Cheong, Alicia; Neo, Zhizhong – International Journal of Virtual and Personal Learning Environments, 2022
Although there is increasing acceptance that personalization improves learning outcomes, there is still limited experimental evidence supporting this claim. The aim of this study was to implement and evaluate the effectiveness of an adaptive recommendation system for Singapore primary and secondary education. The system leverages users trace data…
Descriptors: Academic Achievement, Electronic Learning, Learning Analytics, Learning Processes

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