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Jianzhong Xu – Social Psychology of Education: An International Journal, 2025
This study aims to explore longitudinal associations among homework expectancy, mastery-approach, homework effort, and mathematics achievement involving middle school students over one school year. Results indicated that there was support for a positive reciprocal influence of mastery-approach and effort; greater initial mastery-approach resulted…
Descriptors: Longitudinal Studies, Learning Processes, Mastery Learning, Expectation

Conrad Borchers; Jeroen Ooge; Cindy Peng; Vincent Aleven – Grantee Submission, 2025
Personalized problem selection enhances student practice in tutoring systems. Prior research has focused on transparent problem selection that supports learner control but rarely engages learners in selecting practice materials. We explored how different levels of control (i.e., full AI control, shared control, and full learner control), combined…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Learner Controlled Instruction, Learning Analytics
Jianzhong Xu – European Journal of Psychology of Education, 2024
The present study investigated multilevel models posited to predict student approaches to homework. Participants were 1,072 middle school students in China. Results revealed that deep and surface approaches were positively associated with performance-approach. Furthermore, deep approach to homework was associated negatively with homework cost, yet…
Descriptors: Homework, Hierarchical Linear Modeling, Predictor Variables, Middle School Students
Ngo, Vy; Perez Lacera, Luisa; Closser, Avery Harrison; Ottmar, Erin – Journal of Numerical Cognition, 2023
For students to advance beyond arithmetic, they must learn how to attend to the structure of math notation. This process can be challenging due to students' left-to-right computing tendencies. Brackets are used in mathematics to indicate precedence but can also be used as superfluous cues and perceptual grouping mechanisms in instructional…
Descriptors: Mathematics Skills, Arithmetic, Symbols (Mathematics), Computation
Xu, Jianzhong – European Journal of Psychology of Education, 2021
Whereas it is often a challenge to keep students motivated and interested in academic tasks, it is more of a challenge to have students stay motivated and interested in academic tasks outside school during nonschool hours--homework. Prior research, however, has largely overlooked the reasons or purposes students have for doing homework and their…
Descriptors: Homework, Goal Orientation, Student Interests, Mathematics Achievement
Sun, Meilu; Du, Jianxia; Xu, Jianzhong; Liu, Fangtong – Psychology in the Schools, 2019
The current study validated the Homework Goal Orientation Scale (HGOS) for secondary school students. Results revealed that HGOS consisted of two distinct but related subscales: mastery-approach and performance-approach. Given satisfactory measurement invariance, the latent mean differences were then examined across gender (males vs. females) and…
Descriptors: Homework, Goal Orientation, Gender Differences, Secondary School Students
Leanne Tamm; Sydney M. Risley; Elizabeth Hamik; Angela Combs; Lauren B. Jones; Jamie Patronick; Tat Shing Yeung; Allison K. Zoromski; Amie Duncan – International Journal of Developmental Disabilities, 2024
Background: Academic challenges such as losing/not turning in assignments, misplacing materials, and inefficient studying are common in middle-school students with autism spectrum disorder (ASD) without intellectual disability. Deficits in organization, planning, prioritizing, memory/materials management, and studying skills [i.e. academic…
Descriptors: Academic Achievement, Intelligence Tests, Intervention, Executive Function
Baker, Ryan; Ma, Wei; Zhao, Yuxin; Wang, Shengni; Ma, Zhenjun – International Educational Data Mining Society, 2020
With the development of personalized learning in technological platforms, more data and information are given to instructors on what contents are appropriate for a learner's next step, with an aim of helping them support their students in navigating an optimized learning path that can promote an enhanced learning outcome. In this study, we…
Descriptors: Individualized Instruction, Electronic Learning, Learning Theories, Cognitive Development
Kurt, Uluhan; Tas, Yasemin – Pegem Journal of Education and Instruction, 2019
The aim of this study is to examine how parents' support for their children's science homework and the goal orientation of students in science homework predict their deep learning and management strategies that students use when doing homework. For this purpose, among quantitative research approaches, correlational method was used in the study.…
Descriptors: Homework, Goal Orientation, Learning Strategies, Parent Child Relationship
Leanne Tamm; Sydney M. Risley; Elizabeth Hamik; Angela Combs; Lauren B. Jones; Jamie Patronick; Tat Shing Yeung; Allison K. Zoromski; Amie Duncan – Grantee Submission, 2022
Background: Academic challenges such as losing/not turning in assignments, misplacing materials, and inefficient studying are common in middle-school students with autism spectrum disorder (ASD) without intellectual disability. Deficits in organization, planning, prioritizing, memory/materials management, and studying skills [i.e. academic…
Descriptors: Academic Achievement, Intervention, Executive Function, Autism
Wiginton, Barry Lynn – ProQuest LLC, 2013
This study utilized an explanatory mixed-methods research design to investigate the effect of learning environment on student mathematics achievement, and mathematics self-efficacy, and student learning style in a ninth grade Algebra I classroom. The study also explored the lived experiences of the teachers and students in the three different…
Descriptors: Blended Learning, Technology Uses in Education, Mixed Methods Research, Homework
Baker, Ryan S. J. D.; Goldstein, Adam B.; Heffernan, Neil T. – International Journal of Artificial Intelligence in Education, 2011
Intelligent tutors have become increasingly accurate at detecting whether a student knows a skill, or knowledge component (KC), at a given time. However, current student models do not tell us exactly at which point a KC is learned. In this paper, we present a machine-learned model that assesses the probability that a student learned a KC at a…
Descriptors: Intelligent Tutoring Systems, Mastery Learning, Probability, Knowledge Level