Hassan Khosravi
Biographic Data
| ID | 6789475 |
|---|---|
| NAME | Hassan Khosravi |
| GIVEN NAMES | Hassan |
| FAMILY NAME | Khosravi |
| SIGNATURE | KHOSRAVI H |
| AFFILIATIONS | The University of Queensland |
| ORCID | 0000-0001-8664-6117 |
| VERIFIED | Yes |
| TOTAL WORKS | 19 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 19 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2021 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Generative AI offers more, but students revise less: Comparing the effects of teacher and AI feedback on student essay revisions
Providing high-quality feedback on student writing is essential yet increasingly difficult due to rising class sizes and limited instructional capacity. Generative AI (GenAI) offers a promising and scalable alternative, but its effectiveness compared to traditional teacher feedback, particularly across different prompting techniques, remains uncertain. This study employed a quantitative, randomized three-group experimental design with 70 graduate…
AI assistance in peer feedback provision: Pedagogically sound, but minimally adopted
Engaging students in peer feedback offers significant learning benefits by promoting collaboration, critical thinking, and skill development. However, challenges persist because many students struggle to provide constructive and actionable feedback due to gaps in disciplinary knowledge and pedagogical skills. This study investigates whether Generative AI (GenAI) can help address these challenges by supporting students in delivering high-quality p…
Reclaiming the wind: Indigenous windmills in Iran and their lessons for renewable energy
Emotionally enriched AI-generated feedback: Supporting student well-being without compromising learning
The use of AI-generated feedback in higher education has received growing attention, with most existing research emphasising its accuracy, usefulness in improving student work, and scalability. However, little attention has been paid to the role of emotional cues such as encouragement, praise, and empathetic language in shaping how students perceive and respond to feedback. This study addresses this gap by investigating whether enriching AI-gener…
Enhancing peer feedback provision through user interface scaffolding: A comparative examination of scripting and self-monitoring techniques
Exploring the Impact of Generative AI on Peer Review: Insights from Journal Reviewers
This study investigates the perspectives of 12 journal reviewers from diverse academic disciplines on using large language models (LLMs) in the peer review process. We identified key themes regarding integrating LLMs through qualitative data analysis of verbatim responses to an open-ended questionnaire. Reviewers noted that LLMs can automate tasks such as preliminary screening, plagiarism detection, and language verification, thereby reducing wor…
A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour
Although the field of Artificial Intelligence in Education (AIEd) has a substantial history as a research domain, never before has the rapid evolution of AI applications in education sparked such prominent public discourse. Given the already rapidly growing AIEd literature base in higher education, now is the time to ensure that the field has a solid research and conceptual grounding. This review of reviews is the first comprehensive meta review …
Mapping dust risk under heterogenous vulnerability to dust: The combination of spatial modelling and questionnaire survey
Impact of an instructional guide and examples on the quality of feedback: Insights from a randomised controlled study
While the provision of peer feedback has been widely recommended to enhance learning, many students are inexperienced in this area and would benefit from guidance. This study therefore examines the impact of instructions and examples on the quality of feedback provided by students on peer-developed learning resources produced via an online system, RiPPLE. A randomised controlled experiment with 195 students was conducted to investigate the effica…
Impact of AI assistance on student agency
AI-powered learning technologies are increasingly being used to automate and scaffold learning activities (e.g., personalised reminders for completing tasks, automated real-time feedback for improving writing, or recommendations for when and what to study). While the prevailing view is that these technologies generally have a positive effect on student learning, their impact on students’ agency and ability to self-regulate their learning is under…
Analytics of learning tactics and strategies in an online learnersourcing environment
Beyond item analysis: Connecting student behaviour and performance using e‐assessment logs
Traditional item analyses such as classical test theory (CTT) use exam‐taker responses to assessment items to approximate their difficulty and discrimination. The increased adoption by educational institutions of electronic assessment platforms (EAPs) provides new avenues for assessment analytics by capturing detailed logs of an exam‐taker's journey through their exam. This paper explores how logs created by EAPs can be employed alongside exam‐ta…
Assessment in the age of artificial intelligence
In this paper, we argue that a particular set of issues mars traditional assessment practices. They may be difficult for educators to design and implement; only provide discrete snapshots of performance rather than nuanced views of learning; be unadapted to the particular knowledge, skills, and backgrounds of participants; be tailored to the culture of schooling rather than the cultures schooling is designed to prepare students to enter; and asse…
Explainable Artificial Intelligence in education
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this p…
A new conceptual framework for spatial predictive modelling of land degradation in a semiarid area
Although land degradation (LD) is known as a severe environmental problem, spatial predictive modelling of this phenomenon remains a challenge. This research aimed to develop a new conceptual framework to predict LD susceptibility based on net primary production (NPP) and machine learning approaches. The annual NPP over the period 2001–2020 were obtained using MOD17A3 and the trend of NPP changes was considered to investigate the occurrence sites…
Incorporating AI and learning analytics to build trustworthy peer assessment systems
Peer assessment has been recognised as a sustainable and scalable assessment method that promotes higher‐order learning and provides students with fast and detailed feedback on their work. Despite these benefits, some common concerns and criticisms are associated with the use of peer assessments (eg, scarcity of high‐quality feedback from peer student‐assessors and lack of accuracy in assigning a grade to the assessee) that raise questions about …
The effects of rubrics on evaluative judgement: A randomised controlled experiment
Rubrics have been suggested as a means to foster students’ evaluative judgement, the capacity to appraise their own work and that of others; however, empirical evidence of rubrics’ effectiveness is still emerging. This paper contributes findings from a randomised controlled experiment on the effect of rubrics on evaluative judgement. Participants were randomly assigned to one of two groups: a control group which evaluated peer-authored learning r…
Supporting peer evaluation of student-generated content: A study of three approaches
Engaging students in the creation of learning resources is an effective way of developing a repository of revision items. However, a selection process is needed to separate high- from low-quality resources as some of the materials created by students can be ineffective, inappropriate or incorrect. In this study, we share our experiences and findings in incorporating three approaches for peer evaluation of student-generated content, using an educa…
Repositioning students as co-creators of curriculum for online learning resources
Amid increasing calls for universities to transition to online learning, there is a need to explore how platforms and technology can provide positive student experiences and support learning. In this paper, we discuss the implementation of an online peer learning and recommender platform in a large, multi-campus, first-year health subject (n = 2095). The Recommendation in Personalised Peer Learning Environments (RiPPLE) platform supports student’…
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Repositioning students as co-creators of curriculum for online learning resources
Amid increasing calls for universities to transition to online learning, there is a need to explore how platforms and technology can provide positive student experiences and support learning. In this paper, we discuss the implementation of an online peer learning and recommender platform in a large, multi-campus, first-year health subject (n = 2095). The Recommendation in Personalised Peer Learning Environments (RiPPLE) platform supports student’…
Assessment in the age of artificial intelligence
In this paper, we argue that a particular set of issues mars traditional assessment practices. They may be difficult for educators to design and implement; only provide discrete snapshots of performance rather than nuanced views of learning; be unadapted to the particular knowledge, skills, and backgrounds of participants; be tailored to the culture of schooling rather than the cultures schooling is designed to prepare students to enter; and asse…
Explainable Artificial Intelligence in education
There are emerging concerns about the Fairness, Accountability, Transparency, and Ethics (FATE) of educational interventions supported by the use of Artificial Intelligence (AI) algorithms. One of the emerging methods for increasing trust in AI systems is to use eXplainable AI (XAI), which promotes the use of methods that produce transparent explanations and reasons for decisions AI systems make. Considering the existing literature on XAI, this p…
A new conceptual framework for spatial predictive modelling of land degradation in a semiarid area
Although land degradation (LD) is known as a severe environmental problem, spatial predictive modelling of this phenomenon remains a challenge. This research aimed to develop a new conceptual framework to predict LD susceptibility based on net primary production (NPP) and machine learning approaches. The annual NPP over the period 2001–2020 were obtained using MOD17A3 and the trend of NPP changes was considered to investigate the occurrence sites…
Incorporating AI and learning analytics to build trustworthy peer assessment systems
Peer assessment has been recognised as a sustainable and scalable assessment method that promotes higher‐order learning and provides students with fast and detailed feedback on their work. Despite these benefits, some common concerns and criticisms are associated with the use of peer assessments (eg, scarcity of high‐quality feedback from peer student‐assessors and lack of accuracy in assigning a grade to the assessee) that raise questions about …
The effects of rubrics on evaluative judgement: A randomised controlled experiment
Rubrics have been suggested as a means to foster students’ evaluative judgement, the capacity to appraise their own work and that of others; however, empirical evidence of rubrics’ effectiveness is still emerging. This paper contributes findings from a randomised controlled experiment on the effect of rubrics on evaluative judgement. Participants were randomly assigned to one of two groups: a control group which evaluated peer-authored learning r…
Supporting peer evaluation of student-generated content: A study of three approaches
Engaging students in the creation of learning resources is an effective way of developing a repository of revision items. However, a selection process is needed to separate high- from low-quality resources as some of the materials created by students can be ineffective, inappropriate or incorrect. In this study, we share our experiences and findings in incorporating three approaches for peer evaluation of student-generated content, using an educa…
Analytics of learning tactics and strategies in an online learnersourcing environment
Beyond item analysis: Connecting student behaviour and performance using e‐assessment logs
Traditional item analyses such as classical test theory (CTT) use exam‐taker responses to assessment items to approximate their difficulty and discrimination. The increased adoption by educational institutions of electronic assessment platforms (EAPs) provides new avenues for assessment analytics by capturing detailed logs of an exam‐taker's journey through their exam. This paper explores how logs created by EAPs can be employed alongside exam‐ta…
A meta systematic review of artificial intelligence in higher education: A call for increased ethics, collaboration, and rigour
Although the field of Artificial Intelligence in Education (AIEd) has a substantial history as a research domain, never before has the rapid evolution of AI applications in education sparked such prominent public discourse. Given the already rapidly growing AIEd literature base in higher education, now is the time to ensure that the field has a solid research and conceptual grounding. This review of reviews is the first comprehensive meta review …
Mapping dust risk under heterogenous vulnerability to dust: The combination of spatial modelling and questionnaire survey
Impact of an instructional guide and examples on the quality of feedback: Insights from a randomised controlled study
While the provision of peer feedback has been widely recommended to enhance learning, many students are inexperienced in this area and would benefit from guidance. This study therefore examines the impact of instructions and examples on the quality of feedback provided by students on peer-developed learning resources produced via an online system, RiPPLE. A randomised controlled experiment with 195 students was conducted to investigate the effica…
Impact of AI assistance on student agency
AI-powered learning technologies are increasingly being used to automate and scaffold learning activities (e.g., personalised reminders for completing tasks, automated real-time feedback for improving writing, or recommendations for when and what to study). While the prevailing view is that these technologies generally have a positive effect on student learning, their impact on students’ agency and ability to self-regulate their learning is under…
Emotionally enriched AI-generated feedback: Supporting student well-being without compromising learning
The use of AI-generated feedback in higher education has received growing attention, with most existing research emphasising its accuracy, usefulness in improving student work, and scalability. However, little attention has been paid to the role of emotional cues such as encouragement, praise, and empathetic language in shaping how students perceive and respond to feedback. This study addresses this gap by investigating whether enriching AI-gener…
Enhancing peer feedback provision through user interface scaffolding: A comparative examination of scripting and self-monitoring techniques
Exploring the Impact of Generative AI on Peer Review: Insights from Journal Reviewers
This study investigates the perspectives of 12 journal reviewers from diverse academic disciplines on using large language models (LLMs) in the peer review process. We identified key themes regarding integrating LLMs through qualitative data analysis of verbatim responses to an open-ended questionnaire. Reviewers noted that LLMs can automate tasks such as preliminary screening, plagiarism detection, and language verification, thereby reducing wor…
Generative AI offers more, but students revise less: Comparing the effects of teacher and AI feedback on student essay revisions
Providing high-quality feedback on student writing is essential yet increasingly difficult due to rising class sizes and limited instructional capacity. Generative AI (GenAI) offers a promising and scalable alternative, but its effectiveness compared to traditional teacher feedback, particularly across different prompting techniques, remains uncertain. This study employed a quantitative, randomized three-group experimental design with 70 graduate…
AI assistance in peer feedback provision: Pedagogically sound, but minimally adopted
Engaging students in peer feedback offers significant learning benefits by promoting collaboration, critical thinking, and skill development. However, challenges persist because many students struggle to provide constructive and actionable feedback due to gaps in disciplinary knowledge and pedagogical skills. This study investigates whether Generative AI (GenAI) can help address these challenges by supporting students in delivering high-quality p…
Reclaiming the wind: Indigenous windmills in Iran and their lessons for renewable energy
Computer Science (14 works) · Psychology (10 works) · Intelligent Tutoring Systems and Adaptive Learning (8 works) · Online Learning and Analytics (8 works) · Student Assessment and Feedback (7 works) · Mathematics education (5 works) · Artificial Intelligence (4 works) · Knowledge management (4 works) · Peer Assessment (4 works) · Peer feedback (4 works)