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Jennifer Campbell; Katie Ansell; Tim Stelzer – Physical Review Physics Education Research, 2024
Recent advances in publicly available natural language processors (NLP) may enhance the efficiency of analyzing student short-answer responses in physics education research (PER). We train a state-of-the-art NLP, IBM's Watson, and test its agreement with human coders using two different studies that gathered text responses in which students…
Descriptors: Artificial Intelligence, Physics, Natural Language Processing, Computer Uses in Education
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Leila Mirzoyeva; Zhanna Makhanova; Mona Kamal Ibrahim; Zoya Snezhko – Cogent Education, 2024
The objective of this research is to investigate the effectiveness of integrating natural language processing (NLP) technologies into an English language learning program aimed at enhancing auditory and speaking competencies. The methodology of the research is grounded in the development and testing of the intervention effectiveness of neural…
Descriptors: Foreign Countries, Undergraduate Students, Language Skills, Auditory Training
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Hurwitz, Lisa B.; Macaruso, Paul; Thang, Sarah; Studwell, Jamie – Computers in the Schools, 2022
Unfortunately, far too many American adolescents are unable to read proficiently. The science of reading suggests explicit instruction in both word identification and language processing skills should bolster reading proficiency, but most commercial reading interventions for secondary students focus exclusively on the latter skill area. This study…
Descriptors: Middle School Students, Reading Skills, Computer Software Evaluation, Literacy Education
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Haering, Marlo; Bano, Muneera; Zowghi, Didar; Kearney, Matthew; Maalej, Walid – IEEE Transactions on Learning Technologies, 2021
With the vast number of apps and the complexity of their features, it is becoming challenging for teachers to select a suitable learning app for their courses. Several evaluation frameworks have been proposed in the literature to assist teachers with this selection. The iPAC framework is a well-established mobile learning framework highlighting…
Descriptors: Automation, Courseware, Computer Software Evaluation, Computer Software Selection