ABSTRACT
The assessment of students' performances in Higher Education is one of the essential components of teaching activities. Open-ended tasks allow a more in-depth assessment of students' learning levels, but their evaluation and grading are time-consuming and prone to subjective bias. Since the Covid-19 pandemic, most traditional Higher Education courses converted to online courses;automatic grading and feedback tools and methods (AGFTM) have become critical components of online learning systems, especially with regards to short answers and essays assessment. This work frames the recent advancement in AGFTM through a systematic mapping of the research field and a literature review. This analysis gives an overview of the trends, specific goals, methods, quality of proposals, challenges and limitations in this research area. The results indicate that it is a growing research area, with a large set of techniques involved, but still not mature, where practical implementations have yet to come. © 2023 Elsevier Ltd
ABSTRACT
Due to COVID-19, higher education institutions all over the world transitioned to online learning. The sudden and forced transition to this new learning methodology pushed the Universities to rapidly adequate to the needs, upgrading their digital platforms to comply with the new requirements. In the same way, teachers had to adapt their teaching to fit the new medium’s potentials and limitations. The final receivers of this striking change, the students, had to adequate to the novelty approach, though this process has not been painless. Several difficulties, challenges and opportunities arose in this transition process for students, and the full digital class delivery also stressed them emotively. This study explores University of Foggia students’ perceptions of the emergency online learning. The factors analyzed involved their perception about the University implementation of the online class delivery, their consideration about the future of online learning and their emotional impact in attending courses with this methodology. Quantitative and qualitative data were collected from 3,140 participants. The findings present how students have globally appreciated online learning, but they mostly prefer a blended learning approach. Furthermore, by using segmentation variables, differences emerged among the participants’ groups, indicating online learning can have great potentials, but more complex and integrated approaches are needed to fulfill the different learning needs. © 2022, The Author(s).
ABSTRACT
The assessment of students' performances is one of the essential components of teaching activities, and it poses different challenges to teachers and instructors, especially when considering the grading of responses to open-ended questions (i.e., short-answers or essays). Open-ended tasks allow a more in-depth assessment of students' learning levels, but their evaluation and grading are time-consuming and prone to subjective bias. For these reasons, automatic grading techniques have been studied for a long time, focusing mainly on short-answers rather than long essays. Given the growing popularity of Massive Online Open Courses and the shifting from physical to virtual classrooms environments due to the Covid-19 pandemic, the adoption of questionnaires for evaluating learning performances has rapidly increased. Hence, it is of particular interest to analyze the recent effort of researchers in the development of techniques designed to grade students' responses to open-ended questions. In our work, we consider a systematic literature review focusing on automatic grading of open-ended written assignments. The study encompasses 488 articles published from 1984 to 2021 and aims at understanding the research trends and the techniques to tackle essay automatic grading. Lastly, inferences and recommendations are given for future works in the Learning Analytics field. © 2021 Copyright for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).