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Showing 1 to 15 of 37 results Save | Export
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Dalia Khairy; Nouf Alharbi; Mohamed A. Amasha; Marwa F. Areed; Salem Alkhalaf; Rania A. Abougalala – Education and Information Technologies, 2024
Student outcomes are of great importance in higher education institutions. Accreditation bodies focus on them as an indicator to measure the performance and effectiveness of the institution. Forecasting students' academic performance is crucial for every educational establishment seeking to enhance performance and perseverance of its students and…
Descriptors: Prediction, Tests, Scores, Information Retrieval
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Nesrine Mansouri; Mourad Abed; Makram Soui – Education and Information Technologies, 2024
Selecting undergraduate majors or specializations is a crucial decision for students since it considerably impacts their educational and career paths. Moreover, their decisions should match their academic background, interests, and goals to pursue their passions and discover various career paths with motivation. However, such a decision remains…
Descriptors: Undergraduate Students, Decision Making, Majors (Students), Specialization
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Andrew R. Thompson – Advances in Physiology Education, 2024
The revised two-factor Study Process Questionnaire and the Approaches and Study Skills Inventory for Students are two instruments commonly used to measure student learning approach. Although they are designed to measure similar constructs, it is unclear whether the metrics they provide differ in terms of their real-world classification of learning…
Descriptors: Comparative Analysis, Anatomy, Classification, Cognitive Style
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Yagci, Mustafa – Smart Learning Environments, 2022
Educational data mining has become an effective tool for exploring the hidden relationships in educational data and predicting students' academic achievements. This study proposes a new model based on machine learning algorithms to predict the final exam grades of undergraduate students, taking their midterm exam grades as the source data. The…
Descriptors: Data Analysis, Academic Achievement, Prediction, Undergraduate Students
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Polyzou, Agoritsa; Karypis, George – IEEE Transactions on Learning Technologies, 2019
Developing tools to support students and learning in a traditional or online setting is a significant task in today's educational environment. The initial steps toward enabling such technologies using machine learning techniques focused on predicting the student's performance in terms of the achieved grades. However, these approaches do not…
Descriptors: Prediction, Academic Achievement, Low Achievement, Classification
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Maniktala, Mehak; Cody, Christa; Isvik, Amy; Lytle, Nicholas; Chi, Min; Barnes, Tiffany – Journal of Educational Data Mining, 2020
Determining "when" and "whether" to provide personalized support is a well-known challenge called the assistance dilemma. A core problem in solving the assistance dilemma is the need to discover when students are unproductive so that the tutor can intervene. Such a task is particularly challenging for open-ended domains, even…
Descriptors: Intelligent Tutoring Systems, Problem Solving, Helping Relationship, Prediction
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Yu-Chin, Chiu – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
Recent context-control learning studies have shown that switch costs are reduced in a particular context predicting a high probability of switching as compared to another context predicting a low probability of switching. These context-specific switch probability effects suggest that control of task sets, through experience, can become associated…
Descriptors: Learning Processes, Prior Learning, Task Analysis, Cognitive Ability
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Parhizkar, Amirmohammad; Tejeddin, Golnaz; Khatibi, Toktam – Education and Information Technologies, 2023
Increasing productivity in educational systems is of great importance. Researchers are keen to predict the academic performance of students; this is done to enhance the overall productivity of educational system by effectively identifying students whose performance is below average. This universal concern has been combined with data science…
Descriptors: Algorithms, Grade Point Average, Interdisciplinary Approach, Prediction
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Shillo, Roi; Hoernle, Nicholas; Gal, Kobi – International Educational Data Mining Society, 2019
Creativity is a dynamic process which generates ideas that are both novel and of value. However there is little understanding in what drives creativity in students and how to help teachers or education experts to detect creative thinking. This paper begins to address this gap by providing a platform and experiments for studying how creative…
Descriptors: Geometry, Mathematics Instruction, Visualization, Teaching Methods
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Singer, Gonen; Golan, Maya; Rabin, Neta; Kleper, Dvir – European Journal of Engineering Education, 2020
The purpose of this study is to evaluate how learning disabilities (LDs), in combination with accommodations, affect the performance of a decision-tree to predict the stability of academic behaviour of undergraduate engineering students. Additionally, this study presents several examples to illustrate how a college could use the resultant model to…
Descriptors: Learning Disabilities, Academic Accommodations (Disabilities), Undergraduate Students, Engineering Education
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Tempelaar, Dirk – International Association for Development of the Information Society, 2021
The search for rigor in learning analytics applications has placed survey data in the suspect's corner, favoring more objective trace data. A potential lack of objectivity in survey data is the existence of response styles, the tendency of respondents to answer survey items in a particular biased manner, such as yeah saying or always disagreeing.…
Descriptors: Learning Analytics, Responses, Surveys, Bias
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Wampfler, Rafael; Klingler, Severin; Solenthaler, Barbara; Schinazi, Victor R.; Gross, Markus – International Educational Data Mining Society, 2019
The role of affective states in learning has recently attracted considerable attention in education research. The accurate prediction of affective states can help increase the learning gain by incorporating targeted interventions that are capable of adjusting to changes in the individual affective states of students. Until recently, most work on…
Descriptors: Affective Behavior, Prediction, Problem Solving, Mathematics
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Wampfler, Rafael; Emch, Andreas; Solenthaler, Barbara; Gross, Markus – International Educational Data Mining Society, 2020
Front camera data from tablets used in educational settings offer valuable clues to student behavior, attention, and affective state. Due to the camera's angle of view, the face of the student is partially occluded and skewed. This hinders the ability of experts to adequately capture the learning process and student states. In this paper, we…
Descriptors: Photography, Handheld Devices, Student Behavior, Affective Behavior
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Vogel, Tobias; Carr, Evan W.; Davis, Tyler; Winkielman, Piotr – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2018
Stimuli that capture the central tendency of presented exemplars are often preferred--a phenomenon also known as the classic beauty-in-averageness effect. However, recent studies have shown that this effect can reverse under certain conditions. We propose that a key variable for such ugliness-in-averageness effects is the category structure of the…
Descriptors: Interpersonal Attraction, Preferences, Stimuli, Experiments
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Dolezel, Diane; Shanmugam, Ram; Morrison, Eileen E. – Journal of American College Health, 2020
Objective: To examine the health literacy of college students. Participants: A convenience sample of 245 graduate and undergraduate college students. Methods: During February-April of 2018 participants completed the Short Test of Functional Health Literacy which assessed literacy on two passages describing a thyroid scan, and basic healthcare…
Descriptors: Classification, Health, Literacy, Health Behavior
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