Improving Learning Outcomes: Unlimited vs. Limited Attempts and Time for Supplemental Interactive Online Learning Activities

Abstract

Research indicates the use of interactive online learning (IOL) instructional strategies such as multiple choice, "drag and drop" matching exercises, and case discussions, in online courses enhances learning and results in better learning outcomes. While some instructors might use interactive resources for regular assessments that only allow for one attempt, this experiment examines whether limiting the attempts and the time to complete IOL instructional strategies significantly improves learning outcomes as measured by performance scores on two required exams. The author posits that students who have limited attempts (2) and limited time (20 minutes) will in fact read the chapters before attempting to complete the interactive online activities, thus increasing the correlation between the interactive online activity scores and exam scores. Unlimited attempts and unlimited time provide students with the opportunity to search the textbook for the answers without reading the assigned chapters.As anticipated, the experimental groups with limited attempts and limited time on the IOL activities did demonstrate a statistically significant relationship to combined exam scores. The findings indicate that limited attempts and limited time on formative assessments correlated with exam scores while those formative assessments without constraints did not. Perseverance: Amount of time a student is willing to spend on a given task actively participating in the learning process. It essentially measures motivation for learning. (Carroll, 1989).Carroll (1963) hypothesized the shorter the time needed for learning, the higher the aptitude, with student aptitude related to time required to learn; he believed that all children would learn well but there could be a difference in time

Relationship Between Academic Self-Efficacy and Cognitive Load for Students in Distance Learning

“…The evidence from this study suggests that subjective cognitive load has more impact on performance in such distance learning settings where there is no direct teacher guidance. These results are consistent with those aptitude-treatment interaction studies, which suggest that in particular circumstances teacherdirected instruction reveals advantages (Chen &Chen, 2018;MacKenzie, 2019;Martin et al, 2020). Some of these findings demonstrate that in distance learning settings, specifically students with lower reasoning ability benefit from the teacher-directed instructions (Sahni et al, 2021;Zhampeissova et al, 2020;Ziegler et al, 2020).…”

“…Although studies demonstrate that cognitive overload lowers educational performance, few published studies have examined the consequences of cognitive overload in distance learning settings (Alyushin & Kolobashkina, 2019;Mierlo, Jarodzka, Kirschner, Kirschner, & Kirschner, 2014;Sweller, Van Merrienboer, & Paas, 2019). These findings suggest that more exploration of human collaboration influence the learning process in e-learning is needed (Baum & McPherson, 2019;MacKenzie, 2019;Zhampeissova et al, 2020).…”

Self-pacing and multiple-attempt assessment to address student anxiety in pharmacy calculations

“…It is possible that the observed performance trends among strong and weaker students had a negating effect on correlations between attempt numbers and grades. Weak correlation of unlimited attempts with assessment outcomes [52], and better assessment performance with fewer attempts [53] have also been reported by investigators. Poor performance has been observed despite use of unlimited-attempt learning and assessment strategies [54], including lack of signi cant improvement in knowledge retention of pharmacy calculations with repeated testing despite student perceptions of successful retention [36].…”

Online Assessment in Higher Education: A Systematic Review

“…Automated assessment, including Natural Language Processing, was also used on short-answer questions (Carnegie, 2015;Chen et al, 2018;Ellis & Barber, 2016), or tasks including longer texts (Reilly et al, 2016;Santamaría Lancho et al, 2018;Xian, 2020). Other implementation types included mathematical exercises (Acosta-Gonzaga & Walet, 2018; Yang et al, 2016), programming tasks (Polito & Temperini, 2021;Thille et al,, 2014), or interactive activities (MacKenzie, 2019;Turner & Briggs, 2018). Additional automated assessments included the assessment of language proficiency (Fratter & Marigo, 2018).…”

“…Assessment format: Automated assessment was mostly used for formative assessment and rarely for summative. In 23 cases, an automated assessment was used in the context of solely formative assessment (Acosta-Gonzaga & Walet, 2018; Bacca-Acosta & Avila-Garzon, 2021; Bekmanova et al, 2021;Carpenter et al, 2017;Chen et al, 2021;Förster et al, 2018;Gámiz Sánchez et al, 2014;Hughes et al, 2020;Kühbeck et al, 2019;López-Tocón, 2021;MacKenzie, 2019;Meek et al, 2017;Ogange et al, 2018;Polito & Temperini, 2021;Reilly et al, 2016;Sancho-Vinuesa et al, 2018;Santamaría Lancho et al, 2018;Scalise et al, 2018;Schaffer et al, 2017;Stratling, 2017;Tempelaar, 2020;Wilkinson et al, 2020;Xian, 2020). A total of 15 cases included formative as well as summative assessments (Admiraal et al, 2015;Azevedo et al, 2022;Babo et al, 2020;Carnegie, 2015;Davis et al, 2020;Dermo & Boyne, 2014;Gamage et al, 2019;Guerrero-Roldán & Noguera, 2018;Huisman et al, 2018;Mora et al, 2012;Nguyen et al, 2017;Ortega-Arranz et al, 2019, Wells et al, 2021Yang et al, 2016, Turner & Briggs, 2018 and only six cases used automated assessment exclusively as summative assessment…”