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de Carvalho, Walisson Ferreira; Zárate, Luis Enrique – International Journal of Information and Learning Technology, 2021
Purpose: The paper aims to present a new two stage local causal learning algorithm -- HEISA. In the first stage, the algorithm discoveries the subset of features that better explains a target variable. During the second stage, computes the causal effect, using partial correlation, of each feature of the selected subset. Using this new algorithm,…
Descriptors: Causal Models, Algorithms, Learning Analytics, Correlation
Nesrin Sahin; Juli K. Dixon; Robert C. Schoen – Grantee Submission, 2020
This observational study used data from 270 second-grade students to investigate the association between students' strategy use for multidigit addition and subtraction and their mathematics achievement. Based on strategies they used during a mathematics interview, students were classified into the following strategy groups: (a) standard algorithm,…
Descriptors: Mathematics Achievement, Comparative Analysis, Grade 2, Elementary School Students
William Parker Morgan IV – ProQuest LLC, 2020
Accurate placement into an initial college mathematics course is a key step toward the successful completion of college mathematics and, eventually, a college degree. Conversely, misplacement in mathematics may lead to a reduced likelihood of course completion and degree attainment. This study investigated the ability of two placement models to…
Descriptors: College Mathematics, College Students, Student Placement, Mathematics Achievement
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
Xu Qin; Fan Yang – Grantee Submission, 2022
Causal inference regarding a hypothesized mediation mechanism relies on the assumptions that there are no omitted pretreatment confounders (i.e., confounders preceding the treatment) of the treatment-mediator, treatment-outcome, and mediator-outcome relationships, and there are no posttreatment confounders (i.e., confounders affected by the…
Descriptors: Simulation, Correlation, Inferences, Attribution Theory
Karimov, Ayaz; Saarela, Mirka; Kärkkäinen, Tommi – International Educational Data Mining Society, 2023
Within the last decade, different educational data mining techniques, particularly quantitative methods such as clustering, and regression analysis are widely used to analyze the data from educational games. In this research, we implemented a quantitative data mining technique (clustering) to further investigate students' feedback. Students played…
Descriptors: Student Attitudes, Feedback (Response), Educational Games, Information Retrieval
Hu, Jie; Peng, Yi; Chen, Xiao – IEEE Transactions on Learning Technologies, 2023
The prevalence of information and communication technologies (ICTs) has brought about profound changes in the field of reading, resulting in a large and rapidly growing number of young digital readers. The article intends to identify key contextual factors that synergistically differentiate high and low performers, high and average performers, and…
Descriptors: Decoding (Reading), Educational Technology, Information Technology, Reading Skills
A Sequential Bayesian Changepoint Detection Procedure for Aberrant Behaviors in Computerized Testing
Jing Lu; Chun Wang; Jiwei Zhang; Xue Wang – Grantee Submission, 2023
Changepoints are abrupt variations in a sequence of data in statistical inference. In educational and psychological assessments, it is pivotal to properly differentiate examinees' aberrant behaviors from solution behavior to ensure test reliability and validity. In this paper, we propose a sequential Bayesian changepoint detection algorithm to…
Descriptors: Bayesian Statistics, Behavior Patterns, Computer Assisted Testing, Accuracy
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
Juliana E. Raffaghelli; Bonnie Stewart – OTESSA Conference Proceedings, 2021
In the higher education context, an increasing concern on the technical or instrumental approach permeates attention to academics' data literacies and faculty development. The need for data literacy to deal specifically with the rise of learning analytics in higher education has been raised by some authors, though in spite of some focus on the…
Descriptors: Statistics Education, Faculty Development, Higher Education, Learning Analytics
Amjad Almusaed; Asaad Almssad; Ammar K. Albaaj – International Society for Technology, Education, and Science, 2024
The impact of artificial intelligence (AI) on education and lifelong learning is a topic of significant importance as AI continues to change numerous sectors. This paper aims to critically examine AI's profound effect in these domains. The present research explores the ethical dilemmas and pedagogical approaches relevant to incorporating…
Descriptors: Ethics, Lifelong Learning, Artificial Intelligence, Computer Software
Huo, Rongrong – European Journal of Science and Mathematics Education, 2023
In our investigation of university students' knowledge about real numbers in relation to computer algebra systems (CAS) and how it could be developed in view of their future activity as teachers, we used a computer algorithm as a case to explore the relationship between CAS and the knowledge of real numbers as decimal representations. Our work was…
Descriptors: Numbers, Computer Science Education, Knowledge Level, Algorithms
Farnaz Ronaghi Khameneh – ProQuest LLC, 2017
We introduce an online learning platform that scales collaborative learning. We study the impact of team formation and the team formation process in massive open online classes. We observe that learners prefers team members with similar location, age range and education level. We also observe that team members in more successful teams have diverse…
Descriptors: Cooperative Learning, Electronic Learning, Teamwork, Group Dynamics
Zhang, Jiayi; Andres, Juliana Ma. Alexandra L.; Hutt, Stephen; Baker, Ryan S.; Ocumpaugh, Jaclyn; Nasiar, Nidhi; Mills, Caitlin; Brooks, Jamiella; Sethuaman, Sheela; Young, Tyron – Journal of Educational Data Mining, 2022
Self-regulated learning (SRL) is a critical component of mathematics problem-solving. Students skilled in SRL are more likely to effectively set goals, search for information, and direct their attention and cognitive process so that they align their efforts with their objectives. An influential framework for SRL, the SMART model (Winne, 2017),…
Descriptors: Problem Solving, Mathematics Instruction, Learning Management Systems, Learning Analytics
Zhongzhou Chen; Tom Zhang; Michelle Taub – Journal of Learning Analytics, 2024
The current study measures the extent to which students' self-regulated learning tactics and learning outcomes change as the result of a deliberate, data-driven improvement in the learning design of mastery-based online learning modules. In the original design, students were required to attempt the assessment once before being allowed to access…
Descriptors: Learning Analytics, Algorithms, Instructional Materials, Course Content