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Ishaya Gambo; Faith-Jane Abegunde; Omobola Gambo; Roseline Oluwaseun Ogundokun; Akinbowale Natheniel Babatunde; Cheng-Chi Lee – Education and Information Technologies, 2025
The current educational system relies heavily on manual grading, posing challenges such as delayed feedback and grading inaccuracies. Automated grading tools (AGTs) offer solutions but come with limitations. To address this, "GRAD-AI" is introduced, an advanced AGT that combines automation with teacher involvement for precise grading,…
Descriptors: Automation, Grading, Artificial Intelligence, Computer Assisted Testing
Jackie Tuck – Assessment & Evaluation in Higher Education, 2024
Assessors' perspectives on their evaluative practices remain relatively under-researched. Given evidence that higher education assessment and feedback continue to be problematic, this paper proposes a specific methodological innovation with potential to contribute both to research and practice in this area. It explores the potential of a…
Descriptors: Assignments, Student Evaluation, College Faculty, Undergraduate Students
Terence G. Favero – Advances in Physiology Education, 2025
This article describes the implementation of alternative grading (AG) strategies in an upper-division kinesiology and functional human anatomy course. Traditional point-based grading systems can negatively impact student mental health, decrease intrinsic motivation, and hinder learning. To address these issues, a proficiency-based grading approach…
Descriptors: Alternative Assessment, Grading, Program Implementation, Kinesiology
Meghan Velez; Zackery Reed; Darryl Chamberlain; Cihan Aydiner – Thresholds in Education, 2025
In fewer than two years, generative artificial intelligence (GenAI) has transformed the educational experience for both students and faculty. Writing feedback and evaluation tools like MyEssayFeedback, EssayGrader, and Markr have been released with the promise that faculty will be able to focus more on teaching than simply grading. However, the…
Descriptors: Writing Across the Curriculum, Artificial Intelligence, Feedback (Response), Scores
Sull, Errol Craig – Distance Learning, 2023
Labor-based grading: for many instructors in the world of distance learning this is a new concept, yet it is one that is rapidly growing in acceptance and popularity. First introduced in 1993 by English professor Peter Elbow, the premise of labor-based grading is that instructors weigh assignments based on how much labor--how much…
Descriptors: Grading, Distance Education, Evaluation Methods, Scoring Rubrics
Malik, Ali; Wu, Mike; Vasavada, Vrinda; Song, Jinpeng; Coots, Madison; Mitchell, John; Goodman, Noah; Piech, Chris – International Educational Data Mining Society, 2021
Access to high-quality education at scale is limited by the difficulty of providing student feedback on open-ended assignments in structured domains like programming, graphics, and short response questions. This problem has proven to be exceptionally difficult: for humans, it requires large amounts of manual work, and for computers, until…
Descriptors: Grading, Accuracy, Computer Assisted Testing, Automation
Ramon Lawrence; Sarah Foss; Tatiana Urazova – ACM Transactions on Computing Education, 2023
Objectives: Automatic assessment systems are widely used to provide rapid feedback for students and reduce grading time. Despite the benefits of increased efficiency and improved pedagogical outcomes, an ongoing challenge is mitigating poor student behaviors when interacting with automatic assessment systems including numerous submissions,…
Descriptors: Student Behavior, Evaluation Methods, Technology Uses in Education, Educational Technology
Hao, Qiang; Smith, David H., IV; Ding, Lu; Ko, Amy; Ottaway, Camille; Wilson, Jack; Arakawa, Kai H.; Turcan, Alistair; Poehlman, Timothy; Greer, Tyler – Computer Science Education, 2022
Background and Context: automated feedback for programming assignments has great potential in promoting just-in-time learning, but there has been little work investigating the design of feedback in this context. Objective: to investigate the impacts of different designs of automated feedback on student learning at a fine-grained level, and how…
Descriptors: Computer Science Education, Feedback (Response), Teaching Methods, Comparative Analysis
Evan E. Maicus – ProQuest LLC, 2021
As Computer Science course enrollments have increased over recent years, instructors have turned to automated grading systems to help relieve the burden of processing student assignments. However, the available autograding solutions have generally lacked support for traditionally difficult-to-grade advanced topics courses. In this thesis, I…
Descriptors: Computer Assisted Testing, Automation, Grading, Advanced Courses
Sarah Rutherford – International Journal of Designs for Learning, 2020
This design case documents the motivations, decisions, and results of an experimental course that involved students in the curriculum development process through the use of design thinking methodology. Primary points of student input were determining assignment topics, developing learning objectives, and contributing to the design of grading…
Descriptors: Student Participation, Curriculum Development, Curriculum Design, College Students
Seval Kemal; Aysegül Liman-Kaban – Asian Journal of Distance Education, 2025
This study conducts a comprehensive analysis of the assessment of journal writing in English as a Foreign Language (EFL) at the secondary school level, comparing the performance of a Generative Artificial Intelligence (GenAI) platform with two human graders. Employing a convergent parallel mixed methods design, quantitative data were collected…
Descriptors: Artificial Intelligence, Secondary School Students, Feedback (Response), Writing Assignments
Haldeman, Georgiana; Babes-Vroman Monica; Tjang, Andrew; Nguyen, Thu D. – ACM Transactions on Computing Education, 2021
Autograding systems are being increasingly deployed to meet the challenges of teaching programming at scale. Studies show that formative feedback can greatly help novices learn programming. This work extends an autograder, enabling it to provide formative feedback on programming assignment submissions. Our methodology starts with the design of a…
Descriptors: Student Evaluation, Feedback (Response), Grading, Automation
To, Jessica; Panadero, Ernesto; Carless, David – Assessment & Evaluation in Higher Education, 2022
The analysis of exemplars of different quality is a potentially powerful tool in enabling students to understand assessment expectations and appreciate academic standards. Through a systematic review methodology, this paper synthesises exemplar-based research designs, exemplar implementation and the educational effects of exemplars. The review of…
Descriptors: Research Design, Scoring Rubrics, Peer Evaluation, Self Evaluation (Individuals)
Kat O'Meara – Journal of Response to Writing, 2022
Alternative approaches to assessment in education (many of which are linked to inclusive and antiracist pedagogies) are gaining in popularity across the board, from PK--12 to higher education (Esquivel, 2021; St. Amour, 2020). One such antiracist assessment strategy is using labor-based grading contracts (LBGCs), popularized by Inoue (2019; see…
Descriptors: Writing Evaluation, Grading, Alternative Assessment, Racism
Bruce Bowles – Journal of Response to Writing, 2020
In spite of a host of scholarship pertaining to response and the contexts that surround our response practices, few have studied how everyday classroom texts may inform students' interpretations of teachers' written feedback on their writing. This article examines the results from case studies of six students across two first-year composition…
Descriptors: Feedback (Response), Writing (Composition), Freshman Composition, Context Effect