Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudes
Abstract In recent years, the incorporation of artificial intelligence (AI) into instructional settings has sparked important interest in how it can develop different aspects of language learning, principally in the realm of assessment. While traditional assessment methods have long been central to...
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| Format: | Article |
| Language: | English |
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SpringerOpen
2025-01-01
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| Series: | Language Testing in Asia |
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| Online Access: | https://doi.org/10.1186/s40468-025-00345-0 |
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| author | Mohamad Ahmad Saleem Khasawneh Alaa Aladini Sabah Abdulkader Assi Bemnet Ajanil |
| author_facet | Mohamad Ahmad Saleem Khasawneh Alaa Aladini Sabah Abdulkader Assi Bemnet Ajanil |
| author_sort | Mohamad Ahmad Saleem Khasawneh |
| collection | DOAJ |
| description | Abstract In recent years, the incorporation of artificial intelligence (AI) into instructional settings has sparked important interest in how it can develop different aspects of language learning, principally in the realm of assessment. While traditional assessment methods have long been central to evaluating learners’ progress, the rise of AI tools presents an opportunity to revolutionize assessment practices by providing more personalized and adaptive feedback. This study explored the significance of portfolio assessment in AI-assisted environments, focusing on its impact on academic emotion regulation (AER), mindfulness, and attitudes toward language learning. A total of 69 students (38 in the experimental group (EG) and 31 in the control group (CG) from Bahir Dar University, Bahir Dar, Ethiopia, aged 22–34 years, participated in this quasi-experimental study. The participants, enrolled in the final term of their Bachelor’s program in English Teaching, were randomly assigned to either the EG or CG. The EG engaged in a portfolio assessment approach where AI was employed by the course instructor to review the portfolios and provide continuous, individualized feedback. Conversely, the CG also followed a portfolio assessment approach but relied on traditional teacher-led feedback without AI integration. The study employed pretests and posttests to measure AER and mindfulness levels before and after the intervention. Additionally, an attitude questionnaire was administered to the EG to assess their perceptions of AI-based portfolio assessment. Data analysis included analysis of covariance (ANCOVA), independent sample t-test, and one-sample t-test to determine the effects of the intervention. The findings indicated the potential of AI-assisted portfolio assessment in enhancing AER and mindfulness while fostering positive attitudes toward language learning. By comparing AI-integrated and traditional approaches, this study provides valuable insights into the role of AI in promoting effective and engaging learning experiences in EFL contexts. |
| format | Article |
| id | doaj-art-40b6b3b0a3af4b198d08db7e6ff282e0 |
| institution | Kabale University |
| issn | 2229-0443 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Language Testing in Asia |
| spelling | doaj-art-40b6b3b0a3af4b198d08db7e6ff282e02025-01-26T12:47:25ZengSpringerOpenLanguage Testing in Asia2229-04432025-01-0115111810.1186/s40468-025-00345-0Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudesMohamad Ahmad Saleem Khasawneh0Alaa Aladini1Sabah Abdulkader Assi2Bemnet Ajanil3Special Education Department, King Khalid UniversityDepartment of Education, Dhofar UniversityDepartment of Education, Dhofar UniversityBahir Dar UniversityAbstract In recent years, the incorporation of artificial intelligence (AI) into instructional settings has sparked important interest in how it can develop different aspects of language learning, principally in the realm of assessment. While traditional assessment methods have long been central to evaluating learners’ progress, the rise of AI tools presents an opportunity to revolutionize assessment practices by providing more personalized and adaptive feedback. This study explored the significance of portfolio assessment in AI-assisted environments, focusing on its impact on academic emotion regulation (AER), mindfulness, and attitudes toward language learning. A total of 69 students (38 in the experimental group (EG) and 31 in the control group (CG) from Bahir Dar University, Bahir Dar, Ethiopia, aged 22–34 years, participated in this quasi-experimental study. The participants, enrolled in the final term of their Bachelor’s program in English Teaching, were randomly assigned to either the EG or CG. The EG engaged in a portfolio assessment approach where AI was employed by the course instructor to review the portfolios and provide continuous, individualized feedback. Conversely, the CG also followed a portfolio assessment approach but relied on traditional teacher-led feedback without AI integration. The study employed pretests and posttests to measure AER and mindfulness levels before and after the intervention. Additionally, an attitude questionnaire was administered to the EG to assess their perceptions of AI-based portfolio assessment. Data analysis included analysis of covariance (ANCOVA), independent sample t-test, and one-sample t-test to determine the effects of the intervention. The findings indicated the potential of AI-assisted portfolio assessment in enhancing AER and mindfulness while fostering positive attitudes toward language learning. By comparing AI-integrated and traditional approaches, this study provides valuable insights into the role of AI in promoting effective and engaging learning experiences in EFL contexts.https://doi.org/10.1186/s40468-025-00345-0AIAcademic emotion regulationAttitudePortfolio assessmentMindfulness |
| spellingShingle | Mohamad Ahmad Saleem Khasawneh Alaa Aladini Sabah Abdulkader Assi Bemnet Ajanil Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudes Language Testing in Asia AI Academic emotion regulation Attitude Portfolio assessment Mindfulness |
| title | Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudes |
| title_full | Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudes |
| title_fullStr | Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudes |
| title_full_unstemmed | Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudes |
| title_short | Portfolio assessment in AI-enhanced learning environments: a pathway to emotion regulation, mindfulness, and language learning attitudes |
| title_sort | portfolio assessment in ai enhanced learning environments a pathway to emotion regulation mindfulness and language learning attitudes |
| topic | AI Academic emotion regulation Attitude Portfolio assessment Mindfulness |
| url | https://doi.org/10.1186/s40468-025-00345-0 |
| work_keys_str_mv | AT mohamadahmadsaleemkhasawneh portfolioassessmentinaienhancedlearningenvironmentsapathwaytoemotionregulationmindfulnessandlanguagelearningattitudes AT alaaaladini portfolioassessmentinaienhancedlearningenvironmentsapathwaytoemotionregulationmindfulnessandlanguagelearningattitudes AT sabahabdulkaderassi portfolioassessmentinaienhancedlearningenvironmentsapathwaytoemotionregulationmindfulnessandlanguagelearningattitudes AT bemnetajanil portfolioassessmentinaienhancedlearningenvironmentsapathwaytoemotionregulationmindfulnessandlanguagelearningattitudes |