Maoinithe ag an Aontas Eorpach. Mar sin féin is tuairimí agus tuairimí an údair amháin nó na n-údar amháin iad na tuairimí agus na tuairimí a nochtar agus ní gá go léiríonn siad tuairimí an Aontais Eorpaigh nó na Gníomhaireachta Eorpaí Feidhmiúcháin Oideachais agus Cultúir (EACEA). Ní fhéadfar an tAontas Eorpach ná EACEA a chur i gcuntas astu. Uimhir an tionscadail: 2023-1-NL01-KA220-HED-000155675. Clear Error Identification: The system was effective in clearly identifying errors and providing impactful suggestions for improvement. Impact: The results show that the automatic feedback provided by the system was useful to students to understand their mistakes, to understand the correct statistical method to solve the problem, and to verify the preparation for the final exam. Furthermore, most of the students used the tool iteratively to improve their solutions. Only a few of them used the tool before submitting the solution or just to see the exercises. Implications for practice These findings highlight the AI system's potential in accurately grading student work in data science courses, with slight improvements observed when combining sentence embeddings with distance-based features. Cás-Staidéar 5: Córas AI-Bhunaithe do Mheasúnú Foirmitheach agus Suimitheach i gCúrsaí Eolaíochta Sonraí General information Amelio, A., & De Medio, C. (n.d.), 22 December 2020. An AI-Based System for Formative and Summative Assessment in Data Science Courses, International Journal of Artificial Intelligence in Education (2021) 31:159–185 https://doi.org/10.1007/s40593-020-00230-2 The paper discusses an AI-based system designed for formative and summative assessments in data science courses. This system automates the grading process and provides feedback to both students and professors. This study's aim is to evaluate the system's effectiveness by comparing the time taken for grading, the accuracy of the grading, and the impact on student learning outcomes. Description of case The study evaluated time efficiency on grading manually versus grading with the AI tool, the grading accuracy by comparing the AI tool's accuracy to the manual grading's accuracy, the learning outcomes (the impact of automated feedback of student performance in final exams and the usability of the tool, which was based on the students' feedback on the system's usability. Lessons learned The system was expected to enhance student learning by offering timely and accurate feedback. The Model performance showed that only a slight improvement in performance when distance-based features were included along with sentence embeddings, which suggests that sentence embeddings
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