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Mathias Norqvist; Bert Jonsson; Johan Lithner – Educational Studies in Mathematics, 2025
In mathematics classrooms, it is common practice to work through a series of comparable tasks provided in a textbook. A central question in mathematics education is if tasks should be accompanied with solution methods, or if students should construct the solutions themselves. To explore the impact of these two task designs on student behavior…
Descriptors: Attention, Algorithms, Creativity, Mathematics Education
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Lajoie, Susanne P.; Poitras, Eric G.; Doleck, Tenzin; Huang, Lingyun – Education and Information Technologies, 2023
The present paper builds on the literature that emphasizes the importance of self-regulation for academic learning or self-regulated learning (SRL). SRL research has traditionally focused on count measures of SRL processing events, however, another important measure of SRL is being recognized: time-on-task. The current study captures the influence…
Descriptors: Intelligent Tutoring Systems, Self Management, Time on Task, Correlation
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Tingting Wang; Alejandra Ruiz-Segura; Shan Li; Susanne P. Lajoie – Journal of Computer Assisted Learning, 2024
Background: Scholars have confirmed the vital roles of self-regulated learning (SRL) behaviours in predicting task performance, especially within non-linear technology-rich learning environments (TREs). However, few studies focused on the learning costs (e.g., study effort and time-on-task) related to SRL and the efficiency outcome of SRL (i.e.,…
Descriptors: Problem Solving, Educational Environment, Efficiency, Student Behavior
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González, José Antonio; Giuliano, Mónica; Pérez, Silvia N. – Education and Information Technologies, 2022
Research on impact in student achievement of online homework systems compared to traditional methods is ambivalent. Methodological issues in the study design, besides of technological diversity, can account for this uncertainty. Hypothesis: This study aims to estimate the effect size of homework practice with exercises automatically provided by…
Descriptors: Undergraduate Students, Engineering Education, Electronic Learning, Problem Solving
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Sebastian Brückner; Olga Zlatkin-Troitschanskaia – Empirical Research in Vocational Education and Training, 2024
Positive effects of study progress on the economic knowledge of bachelor students are evident and were often referred to as proof of the validity of tests in the context of a longitudinal analysis. However, differences between "domain-specific" (e.g., semester) or "discipline-specific" (e.g., attended courses) indicators of…
Descriptors: Foreign Countries, Undergraduate Students, Economics Education, Bachelors Degrees
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Dröse, Jennifer; Prediger, Susanne; Neugebauer, Philipp; Delucchi Danhier, Renate; Mertins, Barbara – International Electronic Journal of Mathematics Education, 2021
Syntactic language features of word problems have often been identified by assessment studies and interview studies as potential obstacles in word problem solving. However, students' processes of noticing and interpreting these features have only rarely been investigated in depth because noticing is hard to investigate. Eye-tracking methodology…
Descriptors: Attention, Problem Solving, Word Problems (Mathematics), Syntax
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Cody L. Patterson; Mai Bui; Lino Guajardo; Carlos Acevedo; Brandi Rygaard Gaspard; Rebecca McGraw – North American Chapter of the International Group for the Psychology of Mathematics Education, 2023
We investigate the beliefs that influence middle and high school algebra teachers' appraisals of contextual problems having diverse mathematical and pedagogical features. We asked six teachers to analyze six contextual algebra tasks and indicate how they would apportion instructional time among the six tasks based on their structure, pedagogical…
Descriptors: Mathematics Teachers, Middle School Teachers, High School Teachers, Teacher Attitudes
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Sankaranarayanan, Rajagopal; Kwon, Kyungbin; Cho, Yonjoo – Journal of Interactive Learning Research, 2021
Although collaborative learning is becoming a widely popular instructional method, little research has been undertaken considering human cognitive structures and their influence on the design of collaborative learning tasks. Using cognitive load theory as a theoretical framework in this study, forty-five undergraduate students were assigned to…
Descriptors: Problem Solving, Cooperative Learning, Individual Instruction, Interaction
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Jiun-Wei Guo; Hsiao-Ching She; Meng-Jun Chen; Pei-Yi Tsai – International Journal of Computer-Supported Collaborative Learning, 2023
The individual problem-solving (IPS) and collaborative problem-solving (CPS) have received a lot of attention, yet little research has been conducted to investigate whether CPS and IPS are equally effective in improving students' understanding of physics concepts, problem-solving abilities, and minimizing achievement gaps. Therefore, the present…
Descriptors: Cooperative Learning, Problem Solving, Middle School Students, Grade 8
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Demir, Mustafa; Souldatos, Ioannis – International Journal for Technology in Mathematics Education, 2020
With the advent of information technology, various online homework systems have often been utilized to enhance students' knowledge and skills. Several studies analyzed the effects of web-based homework systems on students' learning through comparing them with paper-pencil homework. However, few studies explored students' homework completion…
Descriptors: Electronic Learning, Homework, Student Behavior, Educational Technology
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Tacoma, Sietske; Heeren, Bastiaan; Jeuring, Johan; Drijvers, Paul – International Journal of Artificial Intelligence in Education, 2020
Hypothesis testing involves a complex stepwise procedure that is challenging for many students in introductory university statistics courses. In this paper we assess how feedback from an Intelligent Tutoring System can address the logic of hypothesis testing and whether such feedback contributes to first-year social sciences students' proficiency…
Descriptors: Hypothesis Testing, Feedback (Response), Intelligent Tutoring Systems, Introductory Courses
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Xenofontos, Nikoletta A.; Hovardas, Tasos; Zacharia, Zacharias C.; Jong, Ton – Journal of Computer Assisted Learning, 2020
We examined student performance in a computer-supported learning environment after students undertook, among others, a graphing task within an inquiry context. Students were assigned in two conditions: (a) Students were given one variable, and they had to select the second one to construct their graph; (b) students were given four variables, and…
Descriptors: Active Learning, Inquiry, Computer Uses in Education, Graphs
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Rodic, Dušica D. – International Baltic Symposium on Science and Technology Education, 2019
Besides measures of students' performances, a valid assessment of students' efficiency in a teaching process should also include measures of invested mental effort. The research presented herein covers several approaches in measuring students' mental effort including 5, 7 and 9-point Likert type scales, time on task, as well as eye tracking…
Descriptors: Science Education, Student Evaluation, Student Behavior, Eye Movements
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Moritz, Julia; Meyerhoff, Hauke S.; Schwan, Stephan – Journal of Educational Psychology, 2020
Previous research has demonstrated that cognitive offloading (i.e., externalizing mental processes) is useful for immediate problem solving. However, long-term effects of cognitive offloading on subsequent problem solving without offloading are remarkably understudied. Our main goal was to investigate the effects of representation control (i.e.,…
Descriptors: Cognitive Processes, Task Analysis, Problem Solving, Visualization
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Hershcovits, Haviv; Vilenchik, Dan; Gal, Kobi – IEEE Transactions on Learning Technologies, 2020
This paper studies students engagement in e-learning environments in which students work independently and solve problems without external supervision. We propose a new method to infer engagement patterns of users in such self-directed environments. We view engagement as a continuous process in time, measured along chosen axes that are derived…
Descriptors: Electronic Learning, Problem Solving, Independent Study, Factor Analysis
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