Comparative analysis of high and low performers’ use of generative AI in EFL academic writing: behavioral patterns and perceptions

Objective: The aim of this study was to compare the effect of state anxiety and self-efficacy among track and field low and high performers. Method: A total of 250 athletes of track and field (100 track, high&low) and (150 field, high&low) were selected as subjects from the Saudi Inter-University participants whose age ranged between 18 to 25 years. Two questionnaires, competitive state anxiety inventory - 2 and sports self-efficacy scale were used for the collection of the data. The mean, the standard deviation, and the t-test were used as the statistical tools to analyze the data. Findings: The results indicated that there were significant differences between the track high and low performers in cognitive anxiety (P ˂ 0.05), self-confidence (P ˂ 0.05) and self-efficacy (P ˂ 0.05). While there was no significant difference between field high and low performers in all the study variables (P ˃ 0.05). The track high performers differed significantly with the field high performers in only self-efficacy (P ˂ 0.05). Whereas, the track low performers had meaningful lower anxiety and self-efficacy than the field low performers (P ˂ 0.05). Applications: It was concluded that the track high performers were more anxious and effective than the track low performers. In addition, the track high performers revealed remarkably greater self-efficacy than the field high performers. Finally, the field low performers had greater anxiety and self-efficacy than the track low performers.

Self-regulated learning as a complex dynamical system: Examining students' STEM learning in a simulation environment

This study examined the temporal co-occurrences of self-regulated learning (SRL) activities and three types of knowledge (i.e., task information, domain knowledge, and metacognitive knowledge) of 34 medical students who solved two tasks of varying complexity in a computer-simulated environment. Specifically, we explored the effects of task complexity on SRL activities, types of knowledge, and their interplay using epistemic network analysis (ENA). We also compared the differences between high and low performers. The results showed that the use of SRL activities, especially the planning and monitoring activities, was more intensive in a difficult task compared to an easy task. Students also used more domain knowledge to solve the difficult task. For both tasks, domain knowledge and metacognitive knowledge co-occurred most frequently, followed by the co-occurrence of domain knowledge and planning. Nevertheless, the interplay of SRL activities and types of knowledge is generally different between the two tasks. Moreover, we found that high performers used significantly more metacognitive knowledge than low performers in the easy task. However, no significant differences were found in the use of SRL activities between high and low performers in both tasks. This study makes theoretical, methodological, and practical contributions to the area of SRL in clinical reasoning.

Lifelong learning is essential for doctors to maintain competence in clinical skills. With performance feedback, learners should be able to formulate specific and achievable learning goals in areas of need. We aimed to determine: (i) the type and specificity of medical student learning goals after a required clinical performance examination; (ii) differences in goal setting among low, average and high performers, and (iii) whether low performers articulate learning goals that are concordant with their learning needs. We conducted a single-site, multi-year, descriptive comparison study. Senior medical students were given performance benchmarks, individual feedback and guidelines on learning goals; each student was subsequently instructed to write two clinical skills learning goals. Investigators coded the learning goals for specificity, categorised the goals, and performed statistical analyses to determine their concordance with student performance level (low, average or high) in data gathering (history taking and physical examination) or communication skills. All 208 students each wrote two learning goals and most (n=200, 96%) wrote two specific learning goals. Nearly two-thirds of low performers in data gathering wrote at least one learning goal that referred to history taking or physical examination; one-third wrote learning goals pertaining to the organisation of the encounter. High performers in data gathering wrote significantly more patient education goals and significantly fewer history-taking goals than average or low performers. Only 50% of low performers in communication wrote learning goals related to communication skills. Low performers in communication were significantly more likely than average or high performers to identify learning goals related to improving performance in future examinations. The provision of performance benchmarking, individual feedback and brief written guidelines helped most senior medical students in our study to write specific clinical skills learning goals. Many low-performing students did not write learning goals concordant with their areas of weakness. Future work might focus on enhancing low performers' continued learning in areas of performance deficits.

While many contemporary studies aim to explore the sources of notable individual differences in arithmetic skills, this study specifically aims to highlight cognitive differences between high and low math performers. Thirty-six undergraduate female students who were identified as either high or low math performers, according to an arithmetic fluency test, were recruited. In the main experiment, EEG recordings were taken, while the participants performed a mental addition task. The mental addition problems were classified as either easy or difficult, and were presented to participants in several forms. The results indicated that problem difficulty increases the gap in accuracy attainment between high and low math performers. Additionally, high performers displayed larger alpha power during mental arithmetic in P7, corresponding to the left parietal lobe. This indicated that combining behavioral and neural data can improve our understanding of the differences between high and low math performers. Interpretations and implications are discussed.

Physical activity post bariatric surgery is associated with greater weight loss outcomes. However, long-term data on patients’ physical activity and physical function levels are currently scarce. PURPOSE: To examine associations between body composition, physical activity, and physical function among obese adults 12–24 months post bariatric surgery. METHODS: Baseline data from patients recruited into an ongoing exercise intervention were analysed. Body composition was assessed using bioelectrical impedance, and waist and hip circumference measurements. Physical activity was estimated using a triaxial accelerometer worn at the waist for 7 days, and physical function was assessed by an incremental shuttle walk test (ISWT), grip strength, and a sit to stand test (STS). Results are presented as mean ± SD. RESULTS: A total of 22 patients with a mean age of 48.1 ± 9.19 years and BMI of 39 ± 5.1kg·m2 were recruited. Mean daily moderate to vigorous physical activity was 33 ± 19.3 min. Grip strength (right: 27.2 ± 8.5 kg; left: 26.8 ± 9.8 kg) was positively correlated with body mass (right: r = 0.621, p = 0.002; left: r = 0.540, p = 0.009) and fat free mass (right: r = 0.838, p < 0.001; left: r = 0.768, p < 0.001) but not fat mass. ISWT (325.9 ± 90.4 cm) was negatively correlated with fat mass (r = -0.520, p = 0.013), hip (r = 0.-486, p = 0.022) and waist (r = -0.521, p = 0.013) circumferences, and the STS test (13.2 ± 5.4 s) was positively correlated with waist circumference (r = 0.422, p = 0.05) but not fat free mass. When sub-divided by median split into high and low performers, the ISWT displayed a significant difference between groups in fat mass (t (20) -2.829, p = 0.010): high performers had a lower fat mass (42.0 ± 6.5 kg) than low performers (53.1 ± 10.9 kg). A significant difference was also observed between low and high performers in the STS test (t (11.5) 2.276, p = 0.043): high performers had a greater fat free mass (63.9 ± 12.5 kg) than low performers (54.3 ± 5.1 kg). CONCLUSION: Higher physical function was associated with favourable body composition assessments 12–24 months after obesity surgery. The role of post-operative physical activity in contributing to body composition and physical function warrants further attention.

BackgroundA major focus of research on the gut microbiota of poultry has been to define signatures of a healthy gut and identify microbiota components that correlate with feed conversion. However, there is a high variation in individual gut microbiota profiles and their association with performance. Population level samples such as dust and pooled excreta could be useful to investigate bacterial signatures associated with productivity at the flock-level. This study was designed to investigate the bacterial signatures of high and low-performing commercial meat chicken farms in dust and pooled excreta samples. Poultry house dust and fresh pooled excreta were collected at days 7, 14, 21, 28 and 35 of age from 8 farms of two Australian integrator companies and 389 samples assessed by 16S ribosomal RNA gene amplicon sequencing. The farms were ranked as low (n = 4) or high performers (n = 4) based on feed conversion rate corrected by body weight.ResultsPermutational analysis of variance based on Bray–Curtis dissimilarities using abundance data for bacterial community structure results showed that company explained the highest variation in the bacterial community structure in excreta (R2 = 0.21, p = 0.001) while age explained the highest variation in the bacterial community structure in dust (R2 = 0.13, p = 0.001). Farm performance explained the least variation in the bacterial community structure in both dust (R2 = 0.03, p = 0.001) and excreta (R2 = 0.01, p = 0.001) samples. However, specific bacterial taxa were found to be associated with high and low performance in both dust and excreta. The bacteria taxa associated with high-performing farms in dust or excreta found in this study were Enterococcus and Candidatus Arthromitus whereas bacterial taxa associated with low-performing farms included Nocardia, Lapillococcus, Brachybacterium, Ruania, Dietzia, Brevibacterium, Jeotgalicoccus, Corynebacterium and Aerococcus.ConclusionsDust and excreta could be useful for investigating bacterial signatures associated with high and low performance in commercial poultry farms. Further studies on a larger number of farms are needed to determine if the bacterial signatures found in this study are reproducible.

Examining the interplay of affect and self regulation in the context of clinical reasoning

This study assesses the effect of mirrors on body image and performance in high and low performing female collegiate ballet students. Twenty-three females enrolled in a beginning ballet class were taught using mirrors, and a second group of 23 beginning females were taught without mirrors. All participants completed the Cash 69-item Body Self-Relations Questionnaire during the first and last class of a 14-week semester. They were videotaped performing in the studio during the fifth and fourteenth weeks. Two ballet teachers independently viewed the videotapes to evaluate the dancers’ rhythmic accuracy, ease and flow of movement, and mastery of steps and alignment, and rated the students’ skill level on a 1-5 scale. For analysis purposes, students whose scores averaged three or higher were categorized as “high performers,” and those who averaged less than three were “low performers.” Two (mirror, non-mirror) by two (high performance, low performance) by two (pre-test, post-test) repeated measures ANOVAs were used to test class differences over the course of the semester. There were significant 3-way interactions for overweight preoccupation (p &lt; 0.01) and body-areas satisfaction (p &lt; 0.05). Low performers increased in overweight preoccupation in the non-mirror class while decreasing in the mirror class. High performers significantly increased in satisfaction for most areas of their body in the non-mirror class, while there were smaller increases for both low and high performers in the mirror class. It is concluded that while use of the mirror has some benefits in training, higher performing dancers feel better about their body image when they do not use the mirror. Lower performers who use the mirror worry less about their weight; those who do not use the mirror worry more. The mirror may provide feedback that helps low performing dancers feel more comfortable with their weight.

Prior research has focused extensively on how emotion tendencies (e.g., duration, frequency, intensity, and valence) affect students’ performance, but little is known about emotion variability (i.e., the fluctuations in emotion states) and how emotion variability affects performance. In this paper, emotion variability was examined among 21 medical students in the context of solving two patient cases of different complexity with BioWorld, a computer-based intelligent tutoring system. Specifically, we examined the influences of task complexity on emotion variability, emotion variability in self-regulated learning (SRL) phases, and the differences in emotion variability between high and low performers. We found that students’ emotion variability varies depending on the SRL phases (i.e., forethought, performance, and self-reflection) and task complexity. High performing students had smaller emotion variability than low performers across the three SRL phases, but the differences in emotion variability were not statistically significant. Moreover, emotion variability in the forethought phase contributed most to high performance when compared to the emotional variability in the performance and self-reflection phases. This study advances theoretical development about emotion variability and provides insights that help explain the mixed results that existed in extant literature.

Business school courses often require team projects, both for pedagogical reasons as well as to prepare students for the kinds of team-based activities that are common in organizations these days. However, social loafing is a common problem in teams, and peer evaluations by team members are sometimes used in such team settings to assess individuals’ contributions. We propose that high and low team performers differ in terms of their ability and motivation to make distinctions in their teammates’ performance, and consequently they differ in how they evaluate their teammates’ performances. Specifically, we predict that high performers will provide evaluations of teammates that distinguish between those who did well and those who performed poorly, and thus high performers’ ratings will exhibit greater variability. In contrast, we predict that low performers will fail to distinguish among teammates’ levels of performance, and thus will provide evaluations that are lower in variability. Using latent growth modeling, we demonstrate that high and low performers do indeed differ as predicted in the variability of the points they allocate to teammates. The pedagogical implications of this positive relationship between team members’ performance and variability in points allocated are discussed.

Background: Athletes who undergo an anterior cruciate ligament (ACL) reconstruction (ACLR) typically follow supervised rehabilitation before returning to sport. Return-to-sport (RTS) readiness is partially determined by RTS testing. It is not known how characteristics of the supervised rehabilitation episode of care relate to performance on RTS testing. Purpose: To compare high, average, and low performers on RTS testing among athletes after ACLR in regard to characteristics of their rehabilitation episode of care. Study Design: Case-control study; Level of evidence 3. Methods: Data from 262 athletes after ACLR (age 20.7 ± 6.7 years; 131 females) who underwent supervised rehabilitation and elective RTS testing were analyzed. Demographic data including the ACL Return-to-Sport Inventory (ACL-RSI) were gathered. RTS testing data included triple-hop symmetry, single-leg vertical jump symmetry, and an assessment of a repeated change-of-direction task for time, the Lower Extremity Functional Test. Athletes were classified as high or low performers if they were in the top (high performers) or bottom quartile (low performers) of at least 2 of the 3 performance measures. Episode of care characteristics included total supervised rehabilitation encounters, episode length, number of unique rehabilitation providers, and frequency of encounters in each quartile. Analyses of covariance with Bonferroni corrections were performed to assess between-group differences with age and sex as covariates. Results: Of the 262 athletes analyzed, 52 were classified as high performers and 46 were classified as low performers. Compared with high performers, low performers had a lower frequency of rehabilitation encounters in the third quartile (−0.39 visits per week; 95% CI, −0.60 to −0.18; P &lt; .01) and fourth quartile (−0.34 visits per week; 95% CI, −0.54 to −0.14; P &lt; .01). Compared with average performers, low performers had a lower frequency of rehabilitation encounters in the third quartile (−0.20 visits per week; 95% CI, −0.36 to −0.03; P = .04). The ACL-RSI score of the high performers was higher than that of average performers (+10.65; 95% CI, 4.17 to 17.12; P &lt; .01) and low performers (+14.82; 95% CI, 6.70 to 22.95; P &lt; .01). Conclusion: Athletes who performed well on RTS tests after ACLR had a significantly higher frequency of rehabilitation encounters during the second half of their rehabilitation episode. Supervised care during the later stages of rehabilitation may have contributed to the more favorable outcomes on RTS tests. Clinicians and patients should consider the timing and distribution of rehabilitation encounters when creating and modifying a plan of care.

Although studies have investigated how students’ problem-solving strategies influence their performance, few explore the comparison between high and low performers. Moreover, there is a lack of empirical evidence on the effect of students’ problem-solving strategies on their performance in visual programming systems. To address this research gap, we developed a visual programming system based on the self-regulated learning model, providing top-down and bottom-up perspectives. We recruited 35 university students to use the visual programming system and collected eye movement data to analyze their problem-solving strategies. Finally, 19 students’ data with the weighted gaze sampling rate exceeding 80% were used to ensure robust data reliability. The results revealed: (1) a positive correlation between performance and visits to the top-down tracking window, and a negative correlation with the bottom-up window; and (2) both high and low performers used both strategies, but high performers favored the top-down approach. The findings suggest that to better support low performers, the visual programming system should provide guidance on applying the top-down strategy for problem-solving. The implications of this study highlight the importance of problem-solving strategies in programming and suggest that incorporating visual scaffolding for the top-down approach may help low performers narrow the gap with high performers.

Trecroci, A, Cavaggioni, L, Rossi, A, Bongiovanni, T, Invernizzi, PL, Formenti, D, and Longo, S. Self-regulated learning assessment in young soccer players: beyond competitive levels. J Strength Cond Res 39(1): e56-e61, 2025-This study explores self-regulated learning (SRL) among young soccer players, transcending the traditional focus on competitive levels. One hundred twenty-four soccer players of regional and provincial levels from under 14 to under 17 age groups voluntarily participated in the study and were combined into a single group. A median-split method based on total time performance was used to separate players into low performers (LPs) and high performers (HPs) from a 90° change of direction dribbling test. The self-regulation of learning-self-report scale for sport practice (SRL-SRS-SP) with a 5-factor solution (planning, reflection, effort, self-efficacy, and self-supervision) and 31 items was used. The score was based on a 1-5 Likert scale. The level of significance was set at p -value < 0.05. The SRL-SRS-SP total score by HP players differed significantly from that of LP players ( p = 0.015). Regarding each subscale, HP players showed significantly higher scores than LP players ( p = 0.011) for planning, whereas no differences were observed for the remaining factors ( p ≥ 0.05). The main observation of this study revealed that HP soccer players had a greater level of engagement in the learning process with a remarkable ability to plan for specific improvement than LP peers. This suggests that the competitive level might not be the sole determinant of differences in SRL. Therefore, strength and conditioning coaches should emphasize metacognitive and motivational components because of their crucial role in enhancing technical and physical performance.

This research aims to investigate the relationship between self-regulated learning awareness, learning behaviors, and learning performance in ubiquitous learning environments. In order to conduct this research, psychometric data about self-regulated learning and log data, such as slide pages that learners read, marker, and annotate, was collected. The accessing activity of device types that stored the learning management system was collected and analyzed by applying path analysis and correlation analysis using data divided into high and low performers. The results indicated that the slide pages which learners read for a duration of between 240 and 299 s had positive effects on the promotion of annotation and the learning performance directly, and albeit indirectly, the enhancement of self-efficacy was affected by other self-regulated learning factors. The results of the correlation analysis indicated that self-efficacy and test anxiety are a key factor that has different effects on the number of the read slide pages in both high and low performers.