Optimized collusion prevention for online exams during social distancing

Steele

Journal of Educational Technology Systems

2021

483

256

The coronavirus disease 2019 (COVID-19) pandemic has changed the landscape of higher education. As academic institutions across the world continue to deal with the global health crisis, there is a need to examine different instructional approaches including online, hybrid, and blended learning methods. This descriptive study provide an in-depth review of the history of blended learning, evolution of hybrid model of instruction, preparedness of faculty with minimal or no experience in online teaching, and lessons learned as faculty worked on navigating COVID-19 situation since early 2020. A fish-bone analysis, a visual and structured approach to identify possible causes of problem, has been used to present the problems faced by faculty during the pandemic. A detailed Strength–Weakness–Opportunities–Threat analysis of blended/hybrid learning has been presented. An evidence-based approach on how instructors can combine the best of both traditional and online instruction to offer engaging learning experiences for students has been described. This research provides valuable insights to faculty and administrators who are preparing to teach during a pandemic and making efforts to academically survive it.

Section: Discussion and Suggestions For Faculty And Administrators —In Covid-19 Post Vaccine And Post-covid-19 Worldmentioning

confidence: 99%

Combining the Best of Online and Face-to-Face Learning: Hybrid and Blended Learning Approach for COVID-19, Post Vaccine, & Post-Pandemic World

Steele

Journal of Educational Technology Systems

2021

483

256

“…Adopting a summative assessment by using verbatim test bank questions (Golden & Kohlbeck, 2020), presenting exam questions in a similar order for all participants (Li et al, 2021), absence of an exam honor code (Corrigan-Gibbs et al, 2015), and unproctored exams (Dendir & Maxwell, 2020) can lead students to cheat in online exams. Further, the study of Bilen and Matros (2020) shows that grading on a curve in online exams increases cheating incidents because it creates a sense of competition among students, and they may feel they have to cheat to do better than the class average to pass the class.…”

Section: Introductionmentioning

confidence: 99%

Violations of and threats to academic integrity in online English language teaching

Çelik

Lancaster

2021

The Literacy Trek

The move to online teaching has brought with it fresh opportunities for students to violate academic integrity. This paper considers such violations from within the domain of online English language teaching, although many of the ideas presented are applicable to other disciplines. The paper reports on a two-part study conducted at a university in Turkey. In the first part, qualitative data collected from students and staff through an online survey form were used to identify a new way of categorizing academic integrity violations. This provided three such categories, namely; exam-related, assignment-related, and online session-related violations. In the second part of the study, 462 students completed a survey related to their attitudes towards both academic integrity violations and the associated threats that may lead to these violations. Although the results revealed students generally presenting a commitment to the fundamental values of academic integrity, many students showed willingness to engage with machine translation software to prepare answers at times when they were expected to be working unaided. The findings underline a need for further consideration about how students are taught and assessed with integrity in an online environment. They also suggest that nuanced discussions about academic integrity need to take place between students and English language teachers.

“…The authors of [14] proposed an anti-collusion approach for on-line exams. They optimized the sequence of questions that are displayed to students in time synchronized slots.…”

Section: Related Workmentioning

confidence: 99%

A Method for Cheating Indication in Unproctored On-Line Exams

Komosný

Rehman

2022

Sensors

COVID-19 has disrupted every field of life and education is not immune to it. Student learning and examinations moved on-line on a few weeks notice, which has created a large workload for academics to grade the assessments and manually detect students’ dishonesty. In this paper, we propose a method to automatically indicate cheating in unproctored on-line exams, when somebody else other than the legitimate student takes the exam. The method is based on the analysis of the student’s on-line traces, which are logged by distance education systems. We work with customized IP geolocation and other data to derive the student’s cheating risk score. We apply the method to approx. 3600 students in 22 courses, where the partial or final on-line exams were unproctored. The found cheating risk scores are presented along with examples of indicated cheatings. The method can be used to select students for knowledge re-validation, or to compare student cheating across courses, age groups, countries, and universities. We compared student cheating risk scores between four academic terms, including two terms of university closure due to COVID-19.