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Putnikovic, Marko; Jovanovic, Jelena – IEEE Transactions on Learning Technologies, 2023
Automatic grading of short answers is an important task in computer-assisted assessment (CAA). Recently, embeddings, as semantic-rich textual representations, have been increasingly used to represent short answers and predict the grade. Despite the recent trend of applying embeddings in automatic short answer grading (ASAG), there are no…
Descriptors: Automation, Computer Assisted Testing, Grading, Natural Language Processing
Ying Fang; Rod D. Roscoe; Danielle S. McNamara – Grantee Submission, 2023
Artificial Intelligence (AI) based assessments are commonly used in a variety of settings including business, healthcare, policing, manufacturing, and education. In education, AI-based assessments undergird intelligent tutoring systems as well as many tools used to evaluate students and, in turn, guide learning and instruction. This chapter…
Descriptors: Artificial Intelligence, Computer Assisted Testing, Student Evaluation, Evaluation Methods
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Schneider, Johannes; Richner, Robin; Riser, Micha – International Journal of Artificial Intelligence in Education, 2023
Autograding short textual answers has become much more feasible due to the rise of NLP and the increased availability of question-answer pairs brought about by a shift to online education. Autograding performance is still inferior to human grading. The statistical and black-box nature of state-of-the-art machine learning models makes them…
Descriptors: Grading, Natural Language Processing, Computer Assisted Testing, Ethics
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Kurdi, Ghader; Leo, Jared; Parsia, Bijan; Sattler, Uli; Al-Emari, Salam – International Journal of Artificial Intelligence in Education, 2020
While exam-style questions are a fundamental educational tool serving a variety of purposes, manual construction of questions is a complex process that requires training, experience, and resources. This, in turn, hinders and slows down the use of educational activities (e.g. providing practice questions) and new advances (e.g. adaptive testing)…
Descriptors: Computer Assisted Testing, Adaptive Testing, Natural Language Processing, Questioning Techniques
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Chen, Dandan; Hebert, Michael; Wilson, Joshua – American Educational Research Journal, 2022
We used multivariate generalizability theory to examine the reliability of hand-scoring and automated essay scoring (AES) and to identify how these scoring methods could be used in conjunction to optimize writing assessment. Students (n = 113) included subsamples of struggling writers and non-struggling writers in Grades 3-5 drawn from a larger…
Descriptors: Reliability, Scoring, Essays, Automation
Li, Haiying; Cai, Zhiqiang; Graesser, Arthur – Grantee Submission, 2018
In this study we developed and evaluated a crowdsourcing-based latent semantic analysis (LSA) approach to computerized summary scoring (CSS). LSA is a frequently used mathematical component in CSS, where LSA similarity represents the extent to which the to-be-graded target summary is similar to a model summary or a set of exemplar summaries.…
Descriptors: Computer Assisted Testing, Scoring, Semantics, Evaluation Methods
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Benli, Ibrahim; Ismailova, Rita – International Technology and Education Journal, 2018
In the 21st century, which is characterized as the Information Age, information access, knowledge quick learning is vital to the development of individuals and societies. With the use of technological innovations in the field of education in the information society, it will be possible to acquire a lasting place in the globalizing world. Distance…
Descriptors: Foreign Countries, Distance Education, Evaluation Methods, Measurement Techniques
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Knight, Simon; Buckingham Shum, Simon; Ryan, Philippa; Sándor, Ágnes; Wang, Xiaolong – International Journal of Artificial Intelligence in Education, 2018
Research into the teaching and assessment of student writing shows that many students find academic writing a challenge to learn, with legal writing no exception. Improving the availability and quality of timely formative feedback is an important aim. However, the time-consuming nature of assessing writing makes it impractical for instructors to…
Descriptors: Writing Evaluation, Natural Language Processing, Legal Education (Professions), Undergraduate Students
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Azevedo, Ana, Ed.; Azevedo, José, Ed. – IGI Global, 2019
E-assessments of students profoundly influence their motivation and play a key role in the educational process. Adapting assessment techniques to current technological advancements allows for effective pedagogical practices, learning processes, and student engagement. The "Handbook of Research on E-Assessment in Higher Education"…
Descriptors: Higher Education, Computer Assisted Testing, Multiple Choice Tests, Guides
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Jordan, Sally; Mitchell, Tom – British Journal of Educational Technology, 2009
A natural language based system has been used to author and mark short-answer free-text assessment tasks. Students attempt the questions online and are given tailored and relatively detailed feedback on incorrect and incomplete responses, and have the opportunity to repeat the task immediately so as to learn from the feedback provided. The answer…
Descriptors: Feedback (Response), Test Items, Natural Language Processing, Teaching Methods
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Jordan, Sally – Practitioner Research in Higher Education, 2009
Feedback on assessment tasks has an important part to play in underpinning student learning. Online assessment enables instantaneous feedback to be given so that the student can act on it immediately. However, concern has been expressed that e-assessment tasks (especially multiple-choice questions) can encourage surface-learning. Several projects…
Descriptors: Computer Assisted Testing, Feedback (Response), Accuracy, Computer Uses in Education
Kotani, Katsunori; Yoshimi, Takehiko; Isahara, Hitoshi – Online Submission, 2010
In textbooks, foreign (second) language reading proficiency is often evaluated through comprehension questions. In case, authentic texts are used as reading material, such questions should be prepared by teachers. However, preparing appropriate questions may be a very demanding task for teachers. This paper introduces a method for automatically…
Descriptors: Foreign Countries, Reading Comprehension, Reading Materials, Predictive Measurement
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Boyer, Kristy Elizabeth, Ed.; Yudelson, Michael, Ed. – International Educational Data Mining Society, 2018
The 11th International Conference on Educational Data Mining (EDM 2018) is held under the auspices of the International Educational Data Mining Society at the Templeton Landing in Buffalo, New York. This year's EDM conference was highly competitive, with 145 long and short paper submissions. Of these, 23 were accepted as full papers and 37…
Descriptors: Data Collection, Data Analysis, Computer Science Education, Program Proposals
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Kalz, Marco; van Bruggen, Jan; Giesbers, Bas; Waterink, Wim; Eshuis, Jannes; Koper, Rob – Campus-Wide Information Systems, 2008
Purpose: The purpose of this paper is twofold: first the paper aims to sketch the theoretical basis for the use of electronic portfolios for prior learning assessment; second it endeavours to introduce latent semantic analysis (LSA) as a powerful method for the computation of semantic similarity between texts and a basis for a new observation link…
Descriptors: Evaluation Methods, Portfolio Assessment, Portfolios (Background Materials), Open Universities
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Hu, Xiangen, Ed.; Barnes, Tiffany, Ed.; Hershkovitz, Arnon, Ed.; Paquette, Luc, Ed. – International Educational Data Mining Society, 2017
The 10th International Conference on Educational Data Mining (EDM 2017) is held under the auspices of the International Educational Data Mining Society at the Optics Velley Kingdom Plaza Hotel, Wuhan, Hubei Province, in China. This years conference features two invited talks by: Dr. Jie Tang, Associate Professor with the Department of Computer…
Descriptors: Data Analysis, Data Collection, Graphs, Data Use
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