Publication Date
| In 2026 | 0 |
| Since 2025 | 3 |
| Since 2022 (last 5 years) | 9 |
| Since 2017 (last 10 years) | 10 |
Descriptor
Source
Author
| Jason M. Harley | 2 |
| Keerat Grewal | 2 |
| Maria Cutumisu | 2 |
| Matthew Moreno | 2 |
| Amani Itani | 1 |
| B. T. G. S. Kumara | 1 |
| Bettina Beech | 1 |
| Birch, Robert Samuel | 1 |
| Dalila Corbari, Sandra | 1 |
| David Lefevre | 1 |
| Duran, Rodrigo | 1 |
| More ▼ | |
Publication Type
| Journal Articles | 10 |
| Reports - Research | 10 |
Education Level
| Higher Education | 10 |
| Postsecondary Education | 10 |
Audience
Location
| Canada | 2 |
| Brazil | 1 |
| Estonia | 1 |
| Sri Lanka | 1 |
| United Kingdom (London) | 1 |
Laws, Policies, & Programs
Assessments and Surveys
What Works Clearinghouse Rating
Kather, Philipp; Duran, Rodrigo; Vahrenhold, Jan – ACM Transactions on Computing Education, 2022
Previous studies on writing and understanding programs presented evidence that programmers beyond a novice stage utilize plans or plan-like structures. Other studies on code composition showed that learners have difficulties with writing, reading, and debugging code where interacting plans are merged into a short piece of code. In this article, we…
Descriptors: Eye Movements, Coding, Algorithms, Schemata (Cognition)
M. P. R. I. R. Silva; R. A. H. M. Rupasingha; B. T. G. S. Kumara – Technology, Pedagogy and Education, 2024
Today, in every academic institution as well as the university system assessing students' performance, identifying the uniqueness of each student and finding solutions to performance problems have become challenging issues. The main purpose of the study is to predict how student performance changes as a result of their behaviours, hobbies,…
Descriptors: Artificial Intelligence, Student Evaluation, Prediction, Recreational Activities
Matthew Moreno; Keerat Grewal; Maria Cutumisu; Jason M. Harley – Educational Psychology Review, 2025
Medical simulations allow medical trainees to work within teams to develop their self-regulated learning (SRL) and socially shared regulated learning (SSRL) skills. These skills are imperative in optimizing performance and teamwork and could be reflected in physiological responses given by learners. This study examines how medical trainees'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Prediction, Algorithms
Matthew Moreno; Keerat Grewal; Maria Cutumisu; Jason M. Harley – Educational Psychology Review, 2025
Medical simulations allow medical trainees to work within teams to develop their self-regulated learning (SRL) and socially shared regulated learning (SSRL) skills. These skills are imperative in optimizing performance and teamwork and could be reflected in physiological responses given by learners. This study examines how medical trainees'…
Descriptors: Artificial Intelligence, Technology Uses in Education, Prediction, Algorithms
Leah Gustilo; Ethel Ong; Minie Rose Lapinid – International Journal for Educational Integrity, 2024
Background: Despite global interest in the interface of Algorithmically-driven writing tools (ADWTs) and academic integrity, empirical data considering educators' perspectives on the challenges, benefits, and policies of ADWTs use remain scarce. Aim: This study responds to calls for empirical investigation concerning the affordances and…
Descriptors: Algorithms, Writing (Composition), Integrity, Teacher Attitudes
Susie Gronseth; Amani Itani; Kathryn Seastrand; Bettina Beech; Marino Bruce; Thamar Solorio; Ioannis Kakadiaris – Journal of Interactive Learning Research, 2025
This study examines the design, implementation, and evaluation of a Digital Educational Escape Room (DEER) titled "Escape from the Doctor's Office," developed to enhance artificial intelligence/machine learning (AI/ML) literacy. Grounded in constructivist pedagogy and behaviorist principles, the DEER was designed using the ADDIE…
Descriptors: Educational Games, Artificial Intelligence, Technological Literacy, Teamwork
Parhizkar, Amirmohammad; Tejeddin, Golnaz; Khatibi, Toktam – Education and Information Technologies, 2023
Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…
Descriptors: Algorithms, Grade Point Average, Interdisciplinary Approach, Prediction
Gomes Junior, José Carmino; Dalila Corbari, Sandra; Kniess, Cláudia Terezinha; Nogueira da Silva, Gérsica Moraes; Piontkewicz, Simone Caroline; de Souza Melo, Maiara; Silveira Carbone, Amanda; Mantovaneli, Oklinger, Jr.; Martins Sobral, Maria do Carmo; Philippi Junior, Arlindo; Fernandez, Felipe; de Aguiar Dutra, Ana Regina; Birch, Robert Samuel; Guerra, José Baltazar Salgueirinho Osório de Andrade; Sampaio, Carlos Alberto Cioce – International Journal of Sustainability in Higher Education, 2023
Purpose: This paper aim to propose a methodological mapping approach for the evaluation of dissertations and theses of graduate programs in the area of environmental sciences in Brazil in relation to the UN sustainable development goals (SDGs). Design/methodology/approach: The research is characterized as exploratory with qualitative/quantitative…
Descriptors: Sustainable Development, Environmental Education, Well Being, Correlation
Pishtari, Gerti; Prieto, Luis P.; Rodriguez-Triana, Maria Jesus; Martinez-Maldonado, Roberto – Journal of Learning Analytics, 2022
This research was triggered by the identified need in literature for large-scale studies about the kinds of designs that teachers create for mobile learning (m-learning). These studies require analyses of large datasets of learning designs. The common approach followed by researchers when analyzing designs has been to manually classify them…
Descriptors: Scaling, Classification, Context Effect, Telecommunications
Robert L. Peach; Sophia N. Yaliraki; David Lefevre; Mauricio Barahona – npj Science of Learning, 2019
The widespread adoption of online courses opens opportunities for analysing learner behaviour and optimising web-based learning adapted to observed usage. Here, we introduce a mathematical framework for the analysis of time-series of online learner engagement, which allows the identification of clusters of learners with similar online temporal…
Descriptors: Learning Analytics, Web Based Instruction, Online Courses, Learner Engagement

Peer reviewed
Direct link
