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Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Interactive Learning Environments, 2024
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined 1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction and 2)…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2023
This paper demonstrated how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. Using a data-driven approach, we examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance (i.e. posttest math knowledge scores) prediction; and…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Soboleva, Elena V.; Zhumakulov, Khurshidzhon K.; Umurkulov, Kayumzhon P.; Ibragimov, Gasanguseyn I.; Kochneva, Lyubov V.; Timofeeva, Maria O. – EURASIA Journal of Mathematics, Science and Technology Education, 2022
The lack of sufficiently developed methodological basis before graduation adversely affects the mathematical competency of future experts that are required by the modern economy. The study aims to investigate the features of the development of a personalized model of teaching mathematics by means of interactive novels to improve the quality of…
Descriptors: Mathematics Instruction, Teaching Methods, Novels, Mathematics Skills
Lee, Jang Ho; Lee, Hansol – Language Awareness, 2023
As digital technology is becoming an increasingly critical component of education, learners' socioeconomic status (SES) and technology use are becoming more important in their learning. In the context of English learning, the present study modeled how learners' SES and their perception of technology use for language learning are linked to their…
Descriptors: Socioeconomic Status, English (Second Language), Second Language Learning, Second Language Instruction
Ji-Eun Lee; Amisha Jindal; Sanika Nitin Patki; Ashish Gurung; Reilly Norum; Erin Ottmar – Grantee Submission, 2022
This paper demonstrates how to apply Machine Learning (ML) techniques to analyze student interaction data collected in an online mathematics game. We examined: (1) how different ML algorithms influenced the precision of middle-school students' (N = 359) performance prediction; and (2) what types of in-game features were associated with student…
Descriptors: Teaching Methods, Algorithms, Mathematics Tests, Computer Games
Rivers, Damian J. – Journal of Educational Computing Research, 2021
Computer-mediated learning initiatives have recently increased due to the novel coronavirus pandemic. Implications are thus created for self-regulation, learning and achievement as computer-mediated learners face unique motivational and metacognitive demands. The current research uses a serial mediation approach to test the effect of goal…
Descriptors: Computer Assisted Instruction, Second Language Learning, Second Language Instruction, English (Second Language)
Sidou, Lais Feltrin; Borges, Endler Marcel – Journal of Chemical Education, 2020
Principal component analysis (PCA) is one of the most important and powerful methods in chemometrics as well as in a wealth of other areas. Running a PCA results in two main elements, the score plot and the loading plot; the score plot provides the location of the samples, and the loading plot indicates correlations among variables, the trends in…
Descriptors: Factor Analysis, Chemistry, Science Instruction, Teaching Methods
Ursavas, Omer Faruk; Reisoglu, Ilknur – International Journal of Information and Learning Technology, 2017
Purpose: The purpose of this paper is to explore the validity of extended technology acceptance model (TAM) in explaining pre-service teachers' Edmodo acceptance and the variation of variables related to TAM among pre-service teachers having different cognitive styles. Design/methodology/approach: Structural equation modeling approach was used to…
Descriptors: Cognitive Style, Structural Equation Models, Models, Validity
Alzahrani, Saad – Journal of Interactive Learning Research, 2021
This article presents a systematic instructional design procedure to develop a Computer-Assisted Vocabulary Acquisition (CAVA) software in a consistent and reliable way. The design process involves ADDIE fundamental elements: Analyse, Design, Development, Implementation, and Evaluation. This article will describe in detail each of the five ADDIE…
Descriptors: Computer Assisted Instruction, Instructional Design, Teaching Methods, Vocabulary Development
Hsu, Liwei – Computer Assisted Language Learning, 2016
This study aims to explore the structural relationships among the variables of EFL (English as a foreign language) learners' perceptual learning styles and Technology Acceptance Model (TAM). Three hundred and forty-one (n = 341) EFL learners were invited to join a self-regulated English pronunciation training program through automatic speech…
Descriptors: Pronunciation, Pronunciation Instruction, Cognitive Style, Statistical Analysis
Foroughi, Cyrus K.; Werner, Nicole E.; McKendrick, Ryan; Cades, David M.; Boehm-Davis, Deborah A. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2016
Previous research has shown that there is a time cost (i.e., a resumption lag) associated with resuming a task following an interruption and that the longer the duration of the interruption, the greater the time cost (i.e., resumption lag increases as interruption duration increases). The memory-for-goals model (Altmann & Trafton, 2002)…
Descriptors: Individual Differences, Short Term Memory, Task Analysis, Attention Control
Ballance, Oliver James – Computer Assisted Language Learning, 2017
One of the most promising avenues of research in computer-assisted language learning is the potential for language learners to make use of language corpora. However, using a corpus requires use of a corpus tool as an interface, typically a concordancer. How such a tool can be made most accessible to learners is an important issue. Specifically,…
Descriptors: Teaching Methods, Indexes, Multivariate Analysis, Classification
Lin, Lijia; Atkinson, Robert K.; Savenye, Wilhelmina C.; Nelson, Brian C. – Interactive Learning Environments, 2016
The purpose of this study was to investigate the impacts of visual cues and different types of self-explanation prompts on learning, cognitive load, and intrinsic motivation in an interactive multimedia environment that was designed to deliver a computer-based lesson about the human cardiovascular system. A total of 126 college students were…
Descriptors: Cues, Outcomes of Education, Multimedia Instruction, Cognitive Ability
Nye, Benjamin D.; Morrison, Donald M.; Samei, Borhan – International Educational Data Mining Society, 2015
Archived transcripts from tens of millions of online human tutoring sessions potentially contain important knowledge about how online tutors help, or fail to help, students learn. However, without ways of automatically analyzing these large corpora, any knowledge in this data will remain buried. One way to approach this issue is to train an…
Descriptors: Tutoring, Instructional Effectiveness, Tutors, Models
Allen, Lauren K.; Eagleson, Roy; de Ribaupierre, Sandrine – Anatomical Sciences Education, 2016
Neuroanatomy is one of the most challenging subjects in anatomy, and novice students often experience difficulty grasping the complex three-dimensional (3D) spatial relationships. This study evaluated a 3D neuroanatomy e-learning module, as well as the relationship between spatial abilities and students' knowledge in neuroanatomy. The study's…
Descriptors: Anatomy, Neurosciences, Undergraduate Students, Medical Students