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Jia Zhu; Xiaodong Ma; Changqin Huang – IEEE Transactions on Learning Technologies, 2024
Knowledge tracing (KT) for evaluating students' knowledge is an essential task in personalized education. More and more researchers have devoted themselves to solving KT tasks, e.g., deep knowledge tracing (DKT), which can capture more sophisticated representations of student knowledge. Nonetheless, these techniques ignore the reconstruction of…
Descriptors: Teaching Methods, Knowledge Level, Algorithms, Attribution Theory
Chenchen Ma; Jing Ouyang; Gongjun Xu – Grantee Submission, 2023
Cognitive Diagnosis Models (CDMs) are a special family of discrete latent variable models that are widely used in educational and psychological measurement. A key component of CDMs is the Q-matrix characterizing the dependence structure between the items and the latent attributes. Additionally, researchers also assume in many applications certain…
Descriptors: Psychological Evaluation, Clinical Diagnosis, Item Analysis, Algorithms
Tianci Liu; Chun Wang; Gongjun Xu – Grantee Submission, 2022
Multidimensional Item Response Theory (MIRT) is widely used in educational and psychological assessment and evaluation. With the increasing size of modern assessment data, many existing estimation methods become computationally demanding and hence they are not scalable to big data, especially for the multidimensional three-parameter and…
Descriptors: Item Response Theory, Computation, Monte Carlo Methods, Algorithms
Fan Ouyang; Tuan Anh Dinh; Weiqi Xu – Journal for STEM Education Research, 2023
Artificial intelligence (AI), as an emerging technology, has been widely used in STEM education to promote the educational assessment. Although AI-driven educational assessment has the potential to assess students' learning automatically and reduce the workload of instructors, there is still a lack of review works to holistically examine the field…
Descriptors: Educational Assessment, Artificial Intelligence, STEM Education, Academic Achievement
Jordan M. Wheeler; Allan S. Cohen; Shiyu Wang – Journal of Educational and Behavioral Statistics, 2024
Topic models are mathematical and statistical models used to analyze textual data. The objective of topic models is to gain information about the latent semantic space of a set of related textual data. The semantic space of a set of textual data contains the relationship between documents and words and how they are used. Topic models are becoming…
Descriptors: Semantics, Educational Assessment, Evaluators, Reliability
Mohamed, Mohamed Hegazy; Abdelgaber, Sayed; Abd-Ellatif, Laila – Journal of Education and e-Learning Research, 2023
Governments and educational authorities around the world are emphasizing performance evaluation of educational systems. Opinion Mining (OM) has gained acceptance among experts in various regions, including the preparation space. The proposed model involves Two modules: the data preprocessing module and the opinion mining module. The main objective…
Descriptors: Educational Practices, Program Evaluation, Opinions, Data Collection
Pooja Rana; Mithilesh Kumar Dubey; Lovi Raj Gupta; Amit Kumar Thakur – Interactive Learning Environments, 2024
In recent years, the system of student learning and academic emotions has been taken seriously to re-engineer the teaching-learning process at all levels of education. This research paper considers both aspects of assessing the translation of knowledge i.e. qualitative and quantitative. In the current scenario, quantitative and qualitative…
Descriptors: Educational Assessment, Outcomes of Education, Models, Evaluation Methods
Sainan Xu; Jing Lu; Jiwei Zhang; Chun Wang; Gongjun Xu – Grantee Submission, 2024
With the growing attention on large-scale educational testing and assessment, the ability to process substantial volumes of response data becomes crucial. Current estimation methods within item response theory (IRT), despite their high precision, often pose considerable computational burdens with large-scale data, leading to reduced computational…
Descriptors: Educational Assessment, Bayesian Statistics, Statistical Inference, Item Response Theory
Wang, Yu; Chiu, Chia-Yi; Köhn, Hans Friedrich – Journal of Educational and Behavioral Statistics, 2023
The multiple-choice (MC) item format has been widely used in educational assessments across diverse content domains. MC items purportedly allow for collecting richer diagnostic information. The effectiveness and economy of administering MC items may have further contributed to their popularity not just in educational assessment. The MC item format…
Descriptors: Multiple Choice Tests, Nonparametric Statistics, Test Format, Educational Assessment