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Han, Insook; Obeid, Iyad; Greco, Devon – Technology, Knowledge and Learning, 2023
This report describes the use of electroencephalography (EEG) to collect online learners' physiological information. Recent technological advancements allow the unobtrusive collection of live neurosignals while learners are engaged in online activities. In the context of multimodal learning analytics, we discuss the potential use of this new…
Descriptors: Learning Analytics, Diagnostic Tests, Metacognition, Brain Hemisphere Functions
Karen C. Fuson; Shannon Kiebler; Robyn Decker – Mathematics Teacher: Learning and Teaching PK-12, 2024
The authors have found that having students learn accessible standard algorithms by explaining them using mathematics drawings increases students' sense of place--value numbers and enables students to articulate their understanding of what is actually happening with the numbers and why. In this article, they will discuss three standard algorithms…
Descriptors: Mathematics Instruction, Multilingualism, Teaching Methods, Teacher Student Relationship
I Made Suarsana; Al Jupri; Didi Suryadi; Elah Nurlaelah; I Gusti Nyoman Yudi Hartawan – Mathematics Teaching Research Journal, 2025
Mathematical and computational thinking (CT) are closely interrelated, yet CT integration into mathematics instruction remains limited. This study aims to analyze the effectiveness of the teaching process for straight-line equations in enhancing students' CT skills and to propose improvements based on the findings. A qualitative case study…
Descriptors: Mathematics Instruction, Teaching Methods, Learning Processes, Instructional Design
Lokkila, Erno; Christopoulos, Athanasios; Laakso, Mikko-Jussi – Informatics in Education, 2023
Prior programming knowledge of students has a major impact on introductory programming courses. Those with prior experience often seem to breeze through the course. Those without prior experience see others breeze through the course and disengage from the material or drop out. The purpose of this study is to demonstrate that novice student…
Descriptors: Prior Learning, Programming, Computer Science Education, Markov Processes
Xiaxia Cao; Yao Zhao; Xiang Li – Education and Information Technologies, 2024
Various studies have been conducted on applying intelligent recognition technology, especially speech recognition technology to improve English learning ability, mostly listening and speaking. However, few studies have touched on how image-to-text recognition technology can be used for writing. The present research was conducted to fill this gap…
Descriptors: Captions, Second Language Learning, Second Language Instruction, Teaching Methods
Li, Xiao; Xu, Hanchen; Zhang, Jinming; Chang, Hua-hua – Journal of Educational and Behavioral Statistics, 2023
The adaptive learning problem concerns how to create an individualized learning plan (also referred to as a learning policy) that chooses the most appropriate learning materials based on a learner's latent traits. In this article, we study an important yet less-addressed adaptive learning problem--one that assumes continuous latent traits.…
Descriptors: Learning Processes, Models, Algorithms, Individualized Instruction
Li, Jiansheng; Lin, Yuyu; Sun, Mingzhu; Shadiev, Rustam – Interactive Learning Environments, 2023
This study examined whether socially shared regulation of learning (SSRL) enhances students' algorithmic thinking performance, promotes learning participation and improves students' learning attitudes through game-based collaborative learning. The students learned algorithmic knowledge and completed programing tasks using Kodu, a new visual…
Descriptors: Cooperative Learning, Game Based Learning, Educational Environment, Algorithms
David B. Nelson; Anaelle Emma Gackiere; Samantha Elizabeth LeGrand; Daniel A. Guberman – Thresholds in Education, 2025
In response to the significant disruption posed by emergent AI technology, we propose a four part framework for teaching and learning practice and development. Rather than focus on the specific technologies of the moment, this framework provides actionable suggestions for individuals with varying views of AI and its positive and negative…
Descriptors: Teaching Methods, Learning Processes, Algorithms, Artificial Intelligence
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
Marie-Monique Schaper; Mariana Aki Tamashiro; Rachel Charlotte Smith; Ole Sejer Iversen – ACM Transactions on Computing Education, 2025
As emerging technologies are rapidly advancing as part of our societies and everyday life, it is crucial to include and empower all students in learning about computing and advanced technologies. These include technical capabilities of algorithms, such as the use of AI, that enable novel interactions between humans and their environment and give…
Descriptors: Inclusion, Artificial Intelligence, Student Empowerment, Algorithms
Harisman, Yulyanti; Dwina, Fitrani; Tasman, Fridgo – Journal on Mathematics Education, 2022
This study aims to design case-based learning with lesson study learning trajectory with the help of teaching aids to make students understand Prim's, Cruscal's, and Djiksra's Algorithms. The validation study was selected because it is a suitable method for this research. The research subjects were 41 Mathematics Education Study Program Students…
Descriptors: Case Method (Teaching Technique), Learning Trajectories, Algorithms, Mathematics Education
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
Abdulkadir Palanci; Rabia Meryem Yilmaz; Zeynep Turan – Education and Information Technologies, 2024
This study aims to reveal the main trends and findings of the studies examining the use of learning analytics in distance education. For this purpose, journal articles indexed in the SSCI index in the Web of Science database were reviewed, and a total of 400 journal articles were analysed within the scope of this study. The systematic review…
Descriptors: Learning Analytics, Distance Education, Educational Trends, Periodicals
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
Liew, Tze Wei; Tan, Su-Mae; Kew, Si Na – Information and Learning Sciences, 2022
Purpose: This study aims to examine if a pedagogical agent's expressed anger, when framed as a feedback cue, can enhance mental effort and learning performance in a multimedia learning environment than expressed happiness. Design/methodology/approach: A between-subjects experiment was conducted in which learners engaged with a multimedia learning…
Descriptors: Teaching Methods, Multimedia Instruction, Psychological Patterns, Emotional Response
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