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Donzallaz, Michelle C.; Haaf, Julia M.; Stevenson, Claire E. – Journal of Experimental Psychology: Learning, Memory, and Cognition, 2023
When producing creative ideas (i.e., ideas that are original and useful) two main processes occur: ideation, where people brainstorm ideas, and evaluation, where they decide if the ideas are creative or not. While much is known about the ideation phase, the cognitive processes involved in creativity evaluation are less clear. In this article, we…
Descriptors: Creativity, Evaluation, Creative Thinking, Models
Hutt, Stephen; Das, Sanchari; Baker, Ryan S. – International Educational Data Mining Society, 2023
The General Data Protection Regulation (GDPR) in the European Union contains directions on how user data may be collected, stored, and when it must be deleted. As similar legislation is developed around the globe, there is the potential for repercussions across multiple fields of research, including educational data mining (EDM). Over the past two…
Descriptors: Data Analysis, Decision Making, Data Collection, Foreign Countries
González-Esparza, Lydia Marion; Jin, Hao-Yue; Lu, Chang; Cutumisu, Maria – AERA Online Paper Repository, 2022
Detecting wheel-spinning behaviors of students who interact with an Intelligent Tutoring System (ITS) is important for generating pertinent and effective feedback and developing more enriching learning experiences. This analysis compares decision tree and bagged tree models of student productive persistence (i.e., mastering a skill) using the…
Descriptors: Student Behavior, Intelligent Tutoring Systems, Feedback (Response), Persistence
Aguas-Hidalgo, Maribel; Quintero-Zazueta, Ricardo – North American Chapter of the International Group for the Psychology of Mathematics Education, 2020
In this research, quotient strategies and their influence on decision-making in situations that involve the comparison of probabilities are analyzed. In order to achieve this, classical probability situations modeled with urns were designed. In each situation, two urns with simple extraction, involving or not proportional relationships, were…
Descriptors: Decision Making, Mathematics Instruction, Models, Secondary School Students
Shi, Yang; Schmucker, Robin; Chi, Min; Barnes, Tiffany; Price, Thomas – International Educational Data Mining Society, 2023
Knowledge components (KCs) have many applications. In computing education, knowing the demonstration of specific KCs has been challenging. This paper introduces an entirely data-driven approach for: (1) discovering KCs; and (2) demonstrating KCs, using students' actual code submissions. Our system is based on two expected properties of KCs: (1)…
Descriptors: Computer Science Education, Data Analysis, Programming, Coding
Khan, Md Akib Zabed; Polyzou, Agoritsa – International Educational Data Mining Society, 2023
Academic advising plays an important role in students' decision-making in higher education. Data-driven methods provide useful recommendations to students to help them with degree completion. Several course recommendation models have been proposed in the literature to recommend courses for the next semester. One aspect of the data that has yet to…
Descriptors: Course Selection (Students), Learning Analytics, Academic Advising, Decision Making
Polyzou, Agoritsa; Nikolakopoulos, Athanasios N.; Karypis, George – International Educational Data Mining Society, 2019
Course selection is a crucial and challenging problem that students have to face while navigating through an undergraduate degree program. The decisions they make shape their future in ways that they cannot conceive in advance. Available departmental sample degree plans are not personalized for each student, and personal discussion time with an…
Descriptors: Markov Processes, Course Selection (Students), Undergraduate Students, Decision Making
The AI Teacher Test: Measuring the Pedagogical Ability of Blender and GPT-3 in Educational Dialogues
Tack, Anaïs; Piech, Chris – International Educational Data Mining Society, 2022
How can we test whether state-of-the-art generative models, such as Blender and GPT-3, are good AI teachers, capable of replying to a student in an educational dialogue? Designing an AI teacher test is challenging: although evaluation methods are much-needed, there is no off-the-shelf solution to measuring pedagogical ability. This paper reports…
Descriptors: Artificial Intelligence, Dialogs (Language), Bayesian Statistics, Decision Making
Patience Stevens; David Plaut – Grantee Submission, 2020
The statistical structure of a given language likely drives our sensitivity to words' morphological structure. The current work begins to investigate to what degree morphological processing effects observed in visual word recognition can be attributed to statistical regularities between orthography and semantics in English, without any prior…
Descriptors: Reading Processes, Word Recognition, Semantics, Written Language
Marilena Panaite; Mihai Dascalu; Amy Johnson; Renu Balyan; Jianmin Dai; Danielle S. McNamara; Stefan Trausan-Matu – Grantee Submission, 2018
Intelligent Tutoring Systems (ITSs) are aimed at promoting acquisition of knowledge and skills by providing relevant and appropriate feedback during students' practice activities. ITSs for literacy instruction commonly assess typed responses using Natural Language Processing (NLP) algorithms. One step in this direction often requires building a…
Descriptors: Intelligent Tutoring Systems, Artificial Intelligence, Algorithms, Decision Making
Ishioka, Takuya; Gotoda, Naka; Alo, Christian; Kunieda, Takayuki; Yaegashi, Rihito; Hayashi, Toshihiro – International Association for Development of the Information Society, 2018
Obtaining tacit knowledge in sports skill learning is difficult. Although, coaches can give their learners easy to understand instructions to obtain the tacit knowledge. The coaches monitor, analyse and interpret learners' physical movement based on the coaches' experiences, then they give the instruction. In self-training without coaches, it is…
Descriptors: Decision Making, Visualization, Video Technology, Athletic Coaches
Morsomme, Raphaël; Alferez, Sofia Vazquez – International Educational Data Mining Society, 2019
Liberal Arts programs are often characterized by their open curriculum. Yet, the abundance of courses available and the highly personalized curriculum are often overwhelming for students who must select courses relevant to their academic interests and suitable to their academic background. This paper presents the course recommender system that we…
Descriptors: Liberal Arts, Course Selection (Students), Courses, College Students
Xu, Peng; Desmarais, Michel C. – International Educational Data Mining Society, 2016
In recent years, substantial improvements were obtained in the effectiveness of data driven algorithms to validate the mapping of items to skills, or the Q-matrix. In the current study we use ensemble algorithms on top of existing Q-matrix refinement algorithms to improve their performance. We combine the boosting technique with a decision tree.…
Descriptors: Matrices, Q Methodology, Psychometrics, Decision Making
Gruver, Nate; Malik, Ali; Capoor, Brahm; Piech, Chris; Stevens, Mitchell L.; Paepcke, Andreas – International Educational Data Mining Society, 2019
Understanding large-scale patterns in student course enrollment is a problem of great interest to university administrators and educational researchers. Yet important decisions are often made without a good quantitative framework of the process underlying student choices. We propose a probabilistic approach to modelling course enrollment…
Descriptors: Models, Course Selection (Students), Enrollment, Decision Making
Kenzhegaliyeva, Makhabbat – Bulgarian Comparative Education Society, 2018
This paper deals with borrowing the German dual vocational training model in Kazakhstan. The aim of the paper is to identify the key issues and challenges of the transfer process. The analysis is based on the model proposed by Phillips and Ochs (2003, 2004) which outlines four stages of policy borrowing: (1) impulses, (2) decision, (3)…
Descriptors: Vocational Education, Technology Transfer, Barriers, Models