SWDYT: So What Do You Think? Canadian students’ attitudes about peerScholar, an online peer-assessment tool

Collimore, Lisa-Marie; Paré, Dwayne E.; Joordens, Steve

doi:10.1007/s10984-014-9170-1

Cited by 15 publications

(6 citation statements)

References 28 publications

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“…26 Collimore and Joordens recently stressed that students tend to have a positive attitude towards the implementation of PA in their courses. 75 Mulder et al explained that students show high satisfaction levels with the PA process, and they believe that it has a positive impact on their learning. 76 According to Kaufman and Schunn, students' perceptions of peer feedback depend on the degree to which they think that the received feedback is unbiased, 77 and, as suggested by Strijbos et al, feedback from a competent person is perceived to be more credible, satisfactory, agreeable, and useful.…”

Section: Discussionmentioning

confidence: 99%

Peer assessment in health professions education

2020

JETHS

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Objectives: The aim of this review is to appraise the available literature on peer assessment, its implementation, students' perceptions and its strengths and limitations. Materials and Methods: A search was prospectively designed to locate the literature relevant to achieving the aims of the review. A pilot review was conducted to ascertain the volume of literature. A wide range of closely related search terms was utilised and combined. Results: Results of the review show that peer assessment is a valuable experience, and most students enjoy the peer assessment process. The mutual process of peer assessment has a positive impact on students' learning; it allows students to evaluate themselves, comment on each other's work and develop more detailed knowledge. It motivates them to achieve better learning outcomes, promotes self-awareness and increases confidence. Students' involvement in the assessment process supports their learning and encourages reflection. Peer assessment improves clinical performance, as it develops critical thinking and problemsolving skills, encourages self-assessment and promotes reflective practice. Conclusions: Similar to all assessment methods, peer assessment has advantages and drawbacks. Concerns about the reliability and validity of peer assessment are raised in the literature. To overcome these drawbacks, authors recommend double marking by faculty members, multiple peer assessors, and clear grading criteria. Furthermore, providing written feedback rather than grades, as well as ensuring anonymity, are recommended in the peer assessment process to ensure a safe environment that can promote students' comfort. Nevertheless, student support throughout the peer assessment process is important for proper implementation.Keywords: Peer assessment, Peer assessment implementation, Assessment in health professions education. IntroductionThe purpose of curricula is to ensure that students study and learn well.1 Evaluations of learning and its quality are functions of the assessment process, which involves collecting and evaluating information to measure students' progress.2,3 Assessment is considered a pivotal element of the curriculum, and it directs and influences learning. Moreover, assessment motivates students and promotes the higher order of thinking skills through testing, measuring and providing feedback.

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Section: Discussionmentioning

confidence: 99%

Peer assessment in health professions education

2020

JETHS

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“…In a generalized peer assessment model, a set of students assess a specific task for an author. The basic tasks in peer assessment systems (e.g., PeerScholar [Collimore et al, 2015] and PeerGrade [Sharma & Potey, 2018]) include self-assessment and peer assessment, followed by the official inspection and grading of the assignment by an instructor. Therefore, the Balanced Allocation algorithm is able to collect the scores of a specific assignment according to three aspects-self-assessment score, peer assessment score, and instructor score.…”

Section: Balanced Allocation Algorithmmentioning

confidence: 99%

Matching Authors and Reviewers in Peer Assessment Based on Authors’ Profiles

2022

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Aim/Purpose: To encourage students’ engagement in peer assessments and provide students with better-quality feedback, this paper describes a technique for author-reviewer matching in peer assessment systems – a Balanced Allocation algorithm. Background: Peer assessment concerns evaluating the work of colleagues and providing feedback on their work. This process is widely applied as a learning method to involve students in the progress of their learning. However, as students have different ability levels, the efficacy of the peer feedback differs from case to case. Thus, peer assessment may not provide satisfactory results for students. In order to mitigate this issue, this paper explains and evaluates an algorithm that matches the author to a set of reviewers. The technique matches authors and reviewers based on how difficult the authors perceived the assignment to be, and the algorithm then matches the selected author to a group of reviewers who may meet the author’s needs in regard to the selected assignment. Methodology: This study used the Multiple Criteria Decision-Making methodology (MCDM) to determine a set of reviewers from among the many available options. The weighted sum method was used because the data that have been collected in user profiles are expressed in the same unit. This study produced an experimental result, examining the algorithm with a real collected dataset and mock-up dataset. In total, there were 240 students in the real dataset, and it contained self-assessment scores, peer scores, and instructor scores for the same assignment. The mock-up dataset created 1000 records for self-assessment scores. The algorithm was evaluated using focus group discussions with 29 programming students and interviews with seven programming instructors. Contribution: This paper contributes to the field in the following two ways. First, an algorithm using a MCDM methodology was proposed to match authors and reviewers in order to facilitate the peer assessment process. In addition, the algorithm used self-assessment as an initial data source to match users, rather than randomly creating reviewer – author pairs. Findings: The findings show the accurate results of the algorithm in matching three reviewers for each author. Furthermore, the algorithm was evaluated based on students’ and instructors’ perspectives. The results are very promising, as they depict a high level of satisfaction for the Balanced Allocation algorithm. Recommendations for Practitioners: We recommend instructors to consider using the Balanced Allocation algorithm to match students in peer assessments, and consequently to benefit from personalizing peer assessment based on students' needs. Recommendation for Researchers: Several MCDM methods could be expanded upon, such as the analytic hierarchy process (AHP) if different attributes are collected, or the artificial neural network (ANN) if fuzzy data is available in the user profile. Each method is suitable for special cases depending on the data available for decision-making. Impact on Society: Suitable pairing in peer assessment would increase the credibility of the peer assessment process and encourage students’ engagement in peer assessments. Future Research: The Balanced Allocation algorithm could be applied using a single group, and a peer assessment with random matching with another group may also be conducted, followed by performing a t-test to determine the impact of matching on students’ performances in the peer assessment activity.

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“…Peer grading, or peer assessment, is defined as "an arrangement for learners to consider and specify the level, value, or quality of a product or performance of other equal-status learners" (Bachelet et al, 2015;Topping, 2009). It is shown in the literature that, when PR is supported by computer technology, students tend to have a positive attitude towards the implementation of online peer assessment in their classrooms and feel benefited from the process (Collimore, Paré, & Joordens, 2015;Luo et al, 2014). Among the many learning benefits for peer assessors, particular interesting are the development of self-learning abilities and the enhancement of critical thinking, which also reinforce the development of student's explanation and argumentation processes (Albano, Capuano, & Pierri, 2017).…”

Section: Literature Overviewmentioning

confidence: 99%

Improving essay peer grading accuracy in massive open online courses using personalized weights from student's engagement and performance

García-Martínez

Cerezo

Bermúdez

et al. 2018

Computer Assisted Learning

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Most massive open online courses (MOOC) use simple schemes for aggregating peer grades, taking the mean or the median, or compute weights from information other than the instructor's opinion about the students' knowledge. To reduce the difference between the instructor and students' aggregated scores, some proposals compute specific weights to aggregate the peer grades. In this work, we analyse the use of students' engagement and performance measures to compute personalized weights and study the validity of the aggregated scores produced by these common functions, mean, and median, together with two others from the information retrieval field, the geometric and harmonic means. To test this procedure, we have analysed data from a MOOC about Philosophy. The course had 1,059 students registered, and 91 participated in a peer review process that consisted in writing an essay and rating three of their peers using a rubric. We compared the aggregation scores obtained using weighted and nonweighted versions of the functions. Our results show that the correlation between the aggregated scores and the instructor's grades can be improved in relation to peer grading, when using the median and weights are computed according to students' performance in chapter tests.

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SWDYT: So What Do You Think? Canadian students’ attitudes about peerScholar, an online peer-assessment tool

Cited by 15 publications

References 28 publications

Peer assessment in health professions education

Peer assessment in health professions education

Matching Authors and Reviewers in Peer Assessment Based on Authors’ Profiles

Improving essay peer grading accuracy in massive open online courses using personalized weights from student's engagement and performance

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