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Peer reviewed
Direct linkDenisa Gandara; Hadis Anahideh – Society for Research on Educational Effectiveness, 2024
Background/Context: Predictive analytics has emerged as an indispensable tool in the education sector, offering insights that can improve student outcomes and inform more equitable policies (Friedler et al., 2019; Kleinberg et al., 2018). However, the widespread adoption of predictive models is hindered by several challenges, including the lack of…
Descriptors: Prediction, Learning Analytics, Ethics, Statistical Bias
Heather A. Davis; Molly Rush; Gregory T. Smith – Journal of American College Health, 2024
Objective: Body dissatisfaction elevates the risk for disordered eating behaviors. Excessive exercise is prevalent among college women and associated with harm. Risk theory posits a bidirectional relationship between risk factors for disordered eating behaviors and the behaviors themselves. This study investigated the longitudinal, reciprocal…
Descriptors: Self Concept, Negative Attitudes, Eating Disorders, Exercise
William R. Nugent – Measurement: Interdisciplinary Research and Perspectives, 2024
Symmetry considerations are important in science, and Group Theory is a theory of symmetry. Classical Measurement Theory is the most used measurement theory in the social and behavioral sciences. In this article, the author uses Matrix Lie (Lee) group theory to formulate a measurement model. Symmetry is defined and illustrated using symmetries of…
Descriptors: Item Response Theory, Measurement Techniques, Models, Simulation
Shiyi Liu; Juan Zheng; Tingting Wang; Zeda Xu; Jie Chao; Shiyan Jiang – AERA Online Paper Repository, 2024
This study introduces a novel approach for predicting student engagement levels in a language-based AI curriculum. The curriculum was integrated into English Language Arts classrooms, in which 106 students from five classes participated five web-based machine learning and text mining modules for 2 weeks. Sentiment and categorical analyses,…
Descriptors: Learner Engagement, Artificial Intelligence, Technology Uses in Education, Language Arts
Download full textEdgar I. Sanchez – ACT Education Corp., 2024
This study examines the predictive validity of high school grade point average and ACT® Composite score on first-year college grade point average prior to and after the onset of the COVID-19 pandemic in 2020. The findings reveal that the predictive power of high school grade point average changed significantly after 2020, suggesting that students…
Descriptors: Prediction, Validity, High School Students, Grade Point Average
Jionghao Lin; Eason Chen; Zifei Han; Ashish Gurung; Danielle R. Thomas; Wei Tan; Ngoc Dang Nguyen; Kenneth R. Koedinger – International Educational Data Mining Society, 2024
Automated explanatory feedback systems play a crucial role in facilitating learning for a large cohort of learners by offering feedback that incorporates explanations, significantly enhancing the learning process. However, delivering such explanatory feedback in real-time poses challenges, particularly when high classification accuracy for…
Descriptors: Artificial Intelligence, Man Machine Systems, Natural Language Processing, Feedback (Response)
Albreiki, Balqis; Habuza, Tetiana; Zaki, Nazar – International Journal of Educational Technology in Higher Education, 2023
Technological advances have significantly affected education, leading to the creation of online learning platforms such as virtual learning environments and massive open online courses. While these platforms offer a variety of features, none of them incorporates a module that accurately predicts students' academic performance and commitment.…
Descriptors: Identification, At Risk Students, Artificial Intelligence, Academic Achievement
Silva, Hernán A.; Quezada, Luis E.; Oddershede, A. M.; Palominos, Pedro I.; O'Brien, Christopher – Journal of College Student Retention: Research, Theory & Practice, 2023
The objective of this paper is the design of a predictive model of students' desertion in Educational Institutions based on the Analytic Hierarchy Process (AHP). The proposed model is based on a weighted sum of individual probabilities of desertion associated with various factors (explanatory variables) by experts in the combined use of the AHP…
Descriptors: Foreign Countries, Prediction, Models, Probability
Fan, Zongwen; Chiong, Raymond – Education and Information Technologies, 2023
Digital capabilities have become increasingly important in this digital age. Within a university setting, digital capability assessment is key to curriculum design and curriculum mapping, given that digital capabilities not only can help students engage and communicate with others but also succeed at work. To the best of our knowledge, however, no…
Descriptors: Course Content, Artificial Intelligence, Technological Literacy, Computer Literacy
Karatas, Kasim; Arpaci, Ibrahim; Yildirim, Yusuf – Education and Urban Society, 2023
This study aimed to predict the culturally responsive teacher roles based on cultural intelligence and self-efficacy using machine learning classification algorithms. The research group consists of 415 teachers from different branches. The Bayes classifier (NaiveBayes), logistic-regression (SMO), lazy-classifier (KStar), meta-classifier…
Descriptors: Prediction, Culturally Relevant Education, Teacher Role, Cultural Awareness
Kerner, Alexander Michael; Biedermann, Uta; Bräuer, Lars; Caspers, Svenja; Doll, Sara; Engelhardt, Maren; Filler, Timm J.; Ghebremedhin, Estifanos; Gundlach, Stefanie; Hayn-Leichsenring, Gregor U.; Heermann, Stephan; Hettwer-Steeger, Ingrid; Hiepe, Laura; Hirt, Bernhard; Hirtler, Lena; Hörmann, Romed; Kulisch, Christoph; Lange, Tobias; Leube, Rudolf; Meuser, Annika Hela; Müller-Gerbl, Magdalena; Nassenstein, Christina; Neckel, Peter H.; Nimtschke, Ute; Paulsen, Friedrich; Prescher, Andreas; Pretterklieber, Michael; Schliwa, Stefanie; Schmidt, Katja; Schmiedl, Andreas; Schomerus, Christof; Schulze-Tanzil, Gundula; Schumacher, Udo; Schumann, Sven; Spindler, Volker; Streicher, Johannes; Tschernig, Thomas; Unverzagt, Axel; Valentiner, Ursula; Viebahn, Christoph; Wedel, Thilo; Weigner, Janet; Weninger, Wolfgang J.; Westermann, Jürgen; Weyers, Imke; Waschke, Jens; Hammer, Niels – Anatomical Sciences Education, 2023
Hands-on courses utilizing preserved human tissues for educational training offer an important pathway to acquire basic anatomical knowledge. Owing to the reevaluation of formaldehyde limits by the European Commission, a joint approach was chosen by the German-speaking anatomies in Europe (Germany, Austria, Switzerland) to find commonalities among…
Descriptors: Anatomy, Hands on Science, Human Body, Laboratory Procedures
Thomas, Rebecca P.; Wittke, Kacie; Blume, Jessica; Mastergeorge, Ann M.; Naigles, Letitia – Journal of Autism and Developmental Disorders, 2023
This longitudinal study examined the degree to which standardized measures of language and natural language samples predicted later language usage in a heterogeneous sample of children with autism spectrum disorder (ASD), and how this relationship is impacted by ASD severity and interventions. Participants with a diagnosis of ASD (N = 54, 41…
Descriptors: Autism Spectrum Disorders, Prediction, Language Usage, Severity (of Disability)
Zhou, Yizhuo; Zhao, Jin; Zhang, Jianjun – Interactive Learning Environments, 2023
On e-learning platforms, most e-learners didn't complete the course successfully. It means that reducing dropout is a critical problem for the sustainability of e-learning. This paper aims to establish a predictive model to describe e-learners' dropout behavior, which can help the commercial e-learning platforms to make appropriate interventions…
Descriptors: Electronic Learning, Prediction, Dropouts, Student Behavior
Supply, Anne-Sophie; Wijns, Nore; Van Dooren, Wim; Onghena, Patrick – Educational Studies in Mathematics, 2023
The many studies with coin-tossing tasks in literature show that the concept of randomness is challenging for adults as well as children. Systematic errors observed in coin-tossing tasks are often related to the representativeness heuristic, which refers to a mental shortcut that is used to judge randomness by evaluating how well a set of random…
Descriptors: Pattern Recognition, Preschool Children, Prediction, Thinking Skills
Seo, Michael; Furukawa, Toshi A.; Karyotaki, Eirini; Efthimiou, Orestis – Research Synthesis Methods, 2023
Clinical prediction models are widely used in modern clinical practice. Such models are often developed using individual patient data (IPD) from a single study, but often there are IPD available from multiple studies. This allows using meta-analytical methods for developing prediction models, increasing power and precision. Different studies,…
Descriptors: Prediction, Models, Patients, Data Analysis
