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Bruce Moghtader – Educational Philosophy and Theory, 2024
This article offers a historical inquiry into behaviorism and its impact on standard of judgement concerning education policies. Drawing from Aldous Huxley's reservation towards behaviorism as a scientific movement that naturalizes the role of control in human affairs, the paper maps the impact of behaviorism on economics of education. By tracing…
Descriptors: Behaviorism, Economics, Human Capital, Educational Policy
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Said Al Faraby; Adiwijaya Adiwijaya; Ade Romadhony – International Journal of Artificial Intelligence in Education, 2024
Questioning plays a vital role in education, directing knowledge construction and assessing students' understanding. However, creating high-level questions requires significant creativity and effort. Automatic question generation is expected to facilitate the generation of not only fluent and relevant but also educationally valuable questions.…
Descriptors: Test Items, Automation, Computer Software, Input Output Analysis
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Alexey Kopyl; Yuki Yew; Jian Wern Ong; Thomas Hiscox; Calem Young; Murat Muradoglu; Tuck Wah Ng – Journal of Chemical Education, 2024
Efforts to encourage laboratory automation through student access to and usage of commercial equipment are hampered by prohibitive acquisition costs. Here, an automated liquid handler using manual pipettes was developed to operate on a commercial hobbyist 3D printer at a cost of US $325. Arising from an iterative design process that ensured…
Descriptors: Science Laboratories, Laboratory Equipment, Computer Peripherals, Printing
Akif Avcu – Malaysian Online Journal of Educational Technology, 2025
This scope-review presents the milestones of how Hierarchical Rater Models (HRMs) become operable to used in automated essay scoring (AES) to improve instructional evaluation. Although essay evaluations--a useful instrument for evaluating higher-order cognitive abilities--have always depended on human raters, concerns regarding rater bias,…
Descriptors: Automation, Scoring, Models, Educational Assessment
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Kamila Misiejuk; Sonsoles López-Pernas; Rogers Kaliisa; Mohammed Saqr – Journal of Learning Analytics, 2025
Generative artificial intelligence (GenAI) has opened new possibilities for designing learning analytics (LA) tools, gaining new insights about student learning processes and their environment, and supporting teachers in assessing and monitoring students. This systematic literature review maps the empirical research of 41 papers utilizing GenAI…
Descriptors: Literature Reviews, Artificial Intelligence, Learning Analytics, Data Collection
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Sandra Nilsson; Elisabet Östlund; Yvonne Thalén; Ulrika Löfkvist – Journal of Speech, Language, and Hearing Research, 2025
Purpose: The Language ENvironment Analysis (LENA) is a technological tool designed for comprehensive recordings and automated analysis of young children's daily language and auditory environments. LENA recordings play a crucial role in both clinical interventions and research, offering insights into the amount of spoken language children are…
Descriptors: Foreign Countries, Family Environment, Toddlers, Oral Language
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Chantelle Gray – Educational Philosophy and Theory, 2025
In contemporary societies, the processes of transindividuation by which knowledges are transformed into cycles and rhythms of metastability have been dramatically short-circuited. In turn, this has provoked the spiritual misery and pseudo-fabulations so prevalent all around us, including our educational contexts. For Stiegler, this is nothing…
Descriptors: Educational Philosophy, Electronic Learning, Automation, Educational Theories
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Haoze Du; Richard Li; Edward Gehringer – International Educational Data Mining Society, 2025
Evaluating the performance of Large Language Models (LLMs) is a critical yet challenging task, particularly when aiming to avoid subjective assessments. This paper proposes a framework for leveraging subjective metrics derived from the class textual materials across different semesters to assess LLM outputs across various tasks. By utilizing…
Descriptors: Artificial Intelligence, Performance, Evaluation, Automation
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Jesper Dannath; Alina Deriyeva; Benjamin Paaßen – International Educational Data Mining Society, 2025
Research on the effectiveness of Intelligent Tutoring Systems (ITSs) suggests that automatic hint generation has the best effect on learning outcomes when hints are provided on the level of intermediate steps. However, ITSs for programming tasks face the challenge to decide on the granularity of steps for feedback, since it is not a priori clear…
Descriptors: Intelligent Tutoring Systems, Programming, Computer Science Education, Undergraduate Students
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Benny G. Johnson; Rachel Van Campenhout; Bill Jerome; María Fernanda Castro; Rodrigo Bistolfi; Jeffrey S. Dittel – International Journal of Artificial Intelligence in Education, 2025
The integration of formative practice questions with textbook content is a well-known method for increasing student learning, and recent advances in artificial intelligence have made automatic question generation a viable option for scaling this learning method to thousands of textbooks. To expand this method to even more students, a parallel…
Descriptors: Foreign Countries, Artificial Intelligence, Spanish, Textbook Content
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Lottridge, Susan; Woolf, Sherri; Young, Mackenzie; Jafari, Amir; Ormerod, Chris – Journal of Computer Assisted Learning, 2023
Background: Deep learning methods, where models do not use explicit features and instead rely on implicit features estimated during model training, suffer from an explainability problem. In text classification, saliency maps that reflect the importance of words in prediction are one approach toward explainability. However, little is known about…
Descriptors: Documentation, Learning Strategies, Models, Prediction
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Nadine Schlomske-Bodenstein; Bernhard Standl; Pablo Pirnay-Dummer – International Association for Development of the Information Society, 2023
The study presented in this paper uses heuristics from computer linguistics and graph theory to analyze a systematic literature review on educational technology. A literature review was conducted to validate an expert-based taxonomy which was developed to ontologize delivered teaching and learning for easy reuse. The sample includes N = 121…
Descriptors: Heuristics, Educational Technology, Literature Reviews, Automation
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Patton, Colleen E.; Wickens, Christopher D.; Smith, C. A. P.; Noble, Kayla M.; Clegg, Benjamin A. – Cognitive Research: Principles and Implications, 2023
In a dynamic decision-making task simulating basic ship movements, participants attempted, through a series of actions, to elicit and identify which one of six other ships was exhibiting either of two hostile behaviors. A high-performing, although imperfect, automated attention aid was introduced. It visually highlighted the ship categorized by an…
Descriptors: Intention, Psychological Patterns, Identification, Automation
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Holmes, Langdon; Crossley, Scott; Sikka, Harshvardhan; Morris, Wesley – Information and Learning Sciences, 2023
Purpose: This study aims to report on an automatic deidentification system for labeling and obfuscating personally identifiable information (PII) in student-generated text. Design/methodology/approach: The authors evaluate the performance of their deidentification system on two data sets of student-generated text. Each data set was human-annotated…
Descriptors: Open Source Technology, Automation, Identification, Confidentiality
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Corinna Jaschek; Julia von Thienen; Kim-Pascal Borchart; Christoph Meinel – Creativity Research Journal, 2023
The automation of creativity measurement is a promising avenue of development, given that classic creativity assessments face challenges such as resource-intensive expert judgments, subjective creativity ratings, and biases in people's self-reports. In this paper, we present a construct validation study for CollaboUse, a test developed to deliver…
Descriptors: Automation, Creativity Tests, Cooperation, Construct Validity
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