Low-performing Students Research Articles

The best of both worlds? A controlled comparison of hybrid and online economics student outcomes

This paper systematically compares undergraduate student learning outcomes between hybrid and online learning formats in Principles of Macroeconomics classes. Exploiting a quasi-experimental design that controls for instructor effects, student characteristics, effort, and experience, we find that students registered for a hybrid section perform worse than similar students in a nearly identical online section across two metrics. We determine that the factors influencing success in each format and attribute lower student performance in hybrid sections to mismatched student expectations of the blended learning format.

Follow the Money or Follow the Mentors?

Since the passage of the Elementary and Secondary Education Act of 1965, over 300 billion dollars have been funneled to schools through Title I funds. Qualifying school districts receive Title I funds to address disparities between disadvantaged students' academic achievement and their less impoverished peers. Substantial research has focused on the impact of funding and other significant factors on student achievement. One such significant factor impacting student achievement is chronic absenteeism, which is associated with lower student performance. Students from disadvantaged environments are more likely to miss school than students from higher-income families. This causal-comparative examination investigates the effects of a mentoring program on disadvantaged students in an urban secondary school. The findings reveal that students participating in mentoring for extended periods demonstrate significantly fewer absences, resulting in higher grade point averages. These findings indicate that low-budget school mentoring programs have a positive impact on absenteeism and student achievement.

GEOAppS: Interactive numerical models of geomorphic processes and application in a post-secondary coastal processes course

The vast extent to which quantitative prerequisites vary among post-secondary geoscience programs often presents a challenge for educators and students alike in courses for which math and physics are foundational. This study discusses the design of GEOAppS, a suite of educational numerical models, and its application toward lowering the barrier-to-entry for quantitative concepts in an upper-level post-secondary coastal processes course. GEOAppS is a software package, built in MATLABⓇ, that provides animated visualizations of course concepts through a graphical user interface. Nineteen students enrolled in the course participated in this study, which used a within-subjects experimental design, in which students alternated between experimental and control treatments, to evaluate the efficacy of GEOAppS at facilitating student understanding of quantitative concepts. GEOAppS was used as the experimental instructional intervention, while complementary, static visualizations (paper handouts) composed the control treatment. For each instructional treatment, students’ learning outcomes were evaluated by: (a) a written exercise completed concurrently to the treatment, and (b) a course quiz administered the following week. Results indicate that students’ performance on the written exercises was higher when using GEOAppS than with static visualizations; however, no significant difference between the two treatments was present in the delayed testing quiz scores. Additionally, the data suggest the existence of aptitude-treatment interaction, in which lower-performing students benefited more from GEOAppS than high-expertise students. An end of study survey of student perceptions showed that most students perceived greater learning from GEOAppS and preferred using the models to the static visuals.

Demographics of Sudanese University Students in Relation to Regional Conflict and Underdevelopment

This research examines regional differences in higher education participation rates in Sudan, and their relations with socioeconomic factors related to development, such as human development index (HDI), women’s status, urban/rural, and source of income. We pay special attention to areas of Sudan where long-running conflicts exist. Two datasets are used: the 2009 National Baseline Household Survey, conducted by Sudan’s Central Bureau of Statistics; and 2016–2017 matriculating students’ data, obtained from Sudan’s Ministry of Education. Regression analysis of the household survey data shows that the most significant factors associated with university attendance are having electricity at home, having a mother who has completed primary education, and being from a non-conflict region. University entrance data shows that young adults from conflict regions lag markedly behind the rest of Sudan in entering students’ academic level. Educational resources in Sudan are densely concentrated in the capital Khartoum, and higher-performing students (especially males) from all regions tend to enroll in universities in Khartoum. Regional universities’ student bodies consist largely of lower-performing students from the same region, especially in conflict regions. Women’s participation in higher education is robust, and women bachelor’s students outnumber men. Our analysis suggests that the following policies could be most effective in improving regional higher education enrollment rates and outcomes: (1) improve infrastructure (electric power in particular) in underserved regions; (2) provide widespread primary education for women; (3) put additional resources into regional universities, to encourage geographical diversity and to better serve women in underdeveloped regions.

Are Clerks Proficient in the Basic Sciences? Assessment of Third-Year Medical Students' Basic Science Knowledge Prior to and at the Completion of Core Clerkship Rotations.

Basic sciences are a cornerstone of undergraduate medical education (UME), yet research indicates that students' basic science knowledge is not well retained. Many UME curricula are increasing the integration between the basic and clinical sciences with the goal of enhancing students' knowledge levels; however, the impact of clerkship training on students' basic science knowledge remains inconclusive. Thus, using clerkship directors' expectations as framework, we aimed to assess third-year medical students' basic science knowledge during clerkship training and evaluate the influence of clerkship training on their basic science knowledge. Using concepts deemed necessary by clerkship directors, we created a basic science assessment for each clerkship rotation. Assessments were distributed to third-year medical students as a pre- and post-test to assess their basic science knowledge prior to and at the completion of each rotation. On average, students retained ≥ 60% of relevant basic science knowledge from pre-clerkship, and neither clerkship rotation order, nor the basic science discipline being assessed, impacted students' basic science knowledge levels. Post-test data revealed that students, on average, reinforced fundamental concepts during clerkship. Interestingly, even though lower-performing students demonstrated the greatest post-test improvement, they still left each rotation with knowledge deficits compared with their highest-performing peers, suggesting that the clinical experience of clerkship appears to be particularly beneficial for lower-performing students, in regard to enhancing their basic science knowledge. Overall, results indicate that earlier exposure to clinical learning in UME, along with integration of basic science education into clerkship, could promote students' basic science knowledge acquisition and retention.

Understanding learner behaviour in online courses with Bayesian modelling and time series characterisation

The intrinsic temporality of learning demands the adoption of methodologies capable of exploiting time-series information. In this study we leverage the sequence data framework and show how data-driven analysis of temporal sequences of task completion in online courses can be used to characterise personal and group learners’ behaviors, and to identify critical tasks and course sessions in a given course design. We also introduce a recently developed probabilistic Bayesian model to learn sequential behaviours of students and predict student performance. The application of our data-driven sequence-based analyses to data from learners undertaking an on-line Business Management course reveals distinct behaviors within the cohort of learners, identifying learners or groups of learners that deviate from the nominal order expected in the course. Using course grades a posteriori, we explore differences in behavior between high and low performing learners. We find that high performing learners follow the progression between weekly sessions more regularly than low performing learners, yet within each weekly session high performing learners are less tied to the nominal task order. We then model the sequences of high and low performance students using the probablistic Bayesian model and show that we can learn engagement behaviors associated with performance. We also show that the data sequence framework can be used for task-centric analysis; we identify critical junctures and differences among types of tasks within the course design. We find that non-rote learning tasks, such as interactive tasks or discussion posts, are correlated with higher performance. We discuss the application of such analytical techniques as an aid to course design, intervention, and student supervision.

Demographics of Sudanese University Students in Relation to Regional Development and Conflict

This research examines regional differences in higher education participation rates in Sudan, and their relations with socioeconomic factors related to development, such as HDI, women's status, urban/rural, and source of income. We pay special attention to areas of Sudan where long-running conflicts exist. Two datasets are used: the 2009 National Baseline Household Survey, conducted by Sudan's Central Bureau of Statistics; and 2016-17 matriculating students' data, obtained from Sudan's Ministry of Education. Regression analysis of the household survey data shows that the most significant factors associated with university attendance are having electricity at home, having a mother who has completed primary education, and being from a non-conflict region. University entrance data shows that young adults from conflict regions lag markedly behind the rest of Sudan in entering students' academic level. Educational resources in Sudan are densely concentrated in the capital Khartoum, and higher-performing students (especially males) from all regions tend to enroll in universities in Khartoum. Regional universities' student bodies consist largely of lower-performing students from the same region, especially in conflict regions. Women's participation in higher education is robust, and women bachelor's students outnumber men. Our analysis suggests that the following policies could be most effective in improving regional higher education enrollment rates and outcomes: (1) improve infrastructure (electric power in particular) in underserved regions; (2) provide widespread primary education for women; (3) Put additional resources into regional universities, to encourage geographical diversity and to better serve women in underdeveloped regions.

Retention of Biomedical Knowledge in Medical Students Predicts USMLE Step 1 Scores.

This article was migrated. The article was marked as recommended. Introduction Medical students are tasked with learning a vast amount of medical knowledge prior to sitting for the USMLE Step 1 exam, a portion of which is either forgotten or becomes inaccessible to memory following each exam. In this study we examined whether accessibility and retention of 1 st-year biochemistry content predicts performance on high stakes exams such as USMLE Step1. Methods First-year medical students were retested on a subset of biochemistry final exam items 10.5 months after sitting for the original exam. Retention was measured as a percentage of the original final exam score. Availability of information was measured with cued recall (i.e., selecting from a list the multiple-choice distractors), while accessibility of information was captured through free recall (without the aid of multiple choice distractors). Results As expected, we found that free recall rates were much lower than cued recall rates, but that students who scored higher on Step 1 had a smaller gap between cued and free recall scores, demonstrating a greater ability to access information than lower-scoring students. Importantly, we also demonstrate that higher-scoring students retained a higher percentage of the original biochemistry material than lower-performing students after 10.5 months, and that the amount information retained in memory was associated with higher scores on Step 1, demonstrating the potential importance of teaching medical school content with the intention of making it stick, especially in students who are not as strong academically. Conclusion The methods employed in this study are straightforward and can be used to compare retention and accessibility of information across medical school courses, and may serve as a guide to curriculum and pedagogical improvements.

Test Score Gaps in Higher Order Thinking Skills: Exploring Instructional Practices to Improve the Skills and Narrow the Gaps

Today’s economy demands higher order thinking skills (HOTS), and the public education system has a critical role in supporting students’ acquisition of HOTS. Yet, numerous studies documented inequity in access to higher quality instruction that promotes HOTS, which could result in wide test score gaps in HOTS. In this study, I examined test score gaps in HOTS and explored instructional practices associated with HOTS, particularly among low-performing students, using large-scale international assessment data from the 2015 Trends in Mathematics and Science Study. I found wide test score gaps in HOTS in mathematics between the lowest and highest socioeconomic status students and between White students and students of color. Instructional practices such as the same ability group work, asking students to work on problems with teacher guidance, and working on problems with no immediately obvious method of solution were found positively associated with the test scores.

Applying Process Mining to Analyze the Behavior of Learners in Online Courses

The most critical challenge in analyzing the data of Massive Open Online Courses (MOOC) using process mining techniques is storing event logs in appropriate formats. In this study, an innovative approach for extraction of MOOC data is described. Thereafter, several process-discovery techniques, i.e., Dotted Chart Analysis, Fuzzy Miner, and Social Network Miner, are applied to the extracted MOOC data. In addition, behavioral studies of high- and low-performance students taking online courses are conducted. These studies considered i) overall behavioral statistics, ii) identification of bottlenecks and loopback behavior through frequency- and time-performance-based approaches, and iii) working together relationships. The results indicated that there are significant behavioral differences between the two groups. We expect that the results of this study will help educators understand students’ behavioral patterns and better organize online course content.

Beneath the Surface: An Investigation of General Chemistry Students' Study Skills to Predict Course Outcomes.

As the conversation in higher education shifts from diversity to inclusion, the attrition rates of students in the STEM fields continues to be a point of discussion. Combined with the demand for expansion in the STEM workforce, various retention reforms have been proposed, implemented, and in some cases integrated into policy following evidence of success. Still, new findings, technological advances, and socio-cultural shifts inevitably necessitate an on-going investigation as to how students approach learning. Among other factors, students who enter college without effective study skills are at much greater risk of being unsuccessful in their coursework. In order to construct an equitable learning environment, a mechanism must be developed to provide underprepared students with access to resources or interventions designed to refine the skills they need to be successful in the course. Early, reliable assessments can provide predictions of individual student outcomes in order to guide the development and implementation of such targeted interventions. In the present study, a model is developed to predict students' odds of success based their study approaches, as measured by their responses to twelve survey items from an existing instrument used in the Chemistry Education Research literature designed to measure students' deep and surface learning approaches. The model's prediction specificity ranges from 66.5% to 86.9% by semester. Two distinct sets of lower-performing students are identified in the data: those who align predominantly with surface approaches to learning versus those who indicate using both deep and surface approaches to learning. This supports the idea of a tailored approach to interventions, rather than a one-size-fits-all solution. Results from this instrument were correlated to students' reported study methods and beliefs.

Teacher Turnover and Financial Incentives in Underprivileged Schools: Evidence from a Compensation Policy in a Developing Country

This paper evaluates the impacts of a policy that introduced a sizeable wage premium (24% to 36%) to teachers at disadvantaged schools on teacher turnover in the public school system in São Paulo, Brazil. We explore a discontinuity at the eligibility rule to identify the policy effect. We find that the wage compensation reduced turnover by 5 p.p. (10.4% over the pre-treatment average). We also show that this policy positively impacted the achievement of low-performing students, but had no effects on average test scores. We rule out alternative explanations, such as reallocation of teachers or direct effects of the wage increase. These results suggest a disruptive effect of teacher turnover on learning, especially on students at the bottom of the test score distribution.

Using reading to teach English as a foreign language

Generally, teaching English as a foreign language (EFL) at elementary, secondary, and university levels in Ecuador focuses primarily on applying teacher-centered approaches or on merely following up on the English textbooks’ scope and sequence. There is much emphasis on developing grammar skills, practicing isolated concepts, and studying different realities depicted in commercial textbooks while neglecting students’ real interests and needs. These traditional practices have created conscious and unconscious conditioning in students, and a significant number of instructors think that English learning is contingent upon grammar rules and the repetition of irrelevant and unnecessary notions, which results in low student academic performance. This descriptive study proposes the use of reading as an educational tool for improving the English teaching and learning process. The researchers applied five reading comprehension tests, three related to General English and two to Academic English, and a confidence level in reading comprehension questionnaire to 37 A1/A2 English third-level university students. Measures of central tendency and variability were used for data analysis. Results show significant improvements in understanding and analyzing texts, high confidence levels for reading in English, and better overall language learning. We suggest making replicas of these didactical practices in other courses offered at the university level.

Socioeconomic inequality and regional disparities in educational achievement: The role of relative poverty

The relationship between PISA 2012 maths test scores and relative poverty was tested in a sample of 35 Italian and Spanish regions, together with a larger sample that included Australian, Belgian, and Canadian regions. The correlation between mean scores in mathematics, adjusted for students' socioeconomic and cultural backgrounds, and poverty rates is ‐−0.84 for the Italian and Spanish sample, and −0.68 for the complete sample. In the regressions, the effect of relative poverty on mean scores in mathematics is highly significant (p < 0.01), robust to different specifications, and independent from students' backgrounds and regional development levels. It is proposed that disparities in average scores in mathematics across regions depend on the shares of low-performing students which, in turn, depend on the degree of relative poverty within regions. The implications for the thesis according to which, in Italy and Spain, regional disparities in educational achievements reflect genetic differences in the IQ of populations are discussed.

Standardized Testing, Use of Assessment Data, and Low Reading Performance of Immigrant and Non-immigrant Students in OECD Countries.

This paper investigates the effects of standardized testing and publication of achievement data on low reading performance for immigrant and non-immigrant students in 30 OECD countries. The paper aims to test hypotheses derived from a principal-agent framework. According to this theoretical perspective, standardized assessments alone should not be associated with reading performance. Instead, the model proposes that the provision of the results to the principle (parents and education authorities) is associated with higher student performance, as this reduces the information asymmetry between principal (parents and educational authorities) and agent (teachers and schools). The results of our analyses of PISA 2009 and 2015 reading data from 422.172 students show that first, the use of standardized achievement tests alone was not associated with the risk of low performance. Second, making the results of standardized tests available to the public was associated with a decreased risk of low reading performance among all students, and, third, particularly among first generation immigrant students. These results were robust across various modeling approaches. In accordance with the predictions from the principal-agent framework, our findings suggest that the mere implementation of standardized assessments has no effects on low performance. Testing along with the public provision of the testing results, which decreases the information asymmetry between schools and teachers on the one hand and parents and education authorities on the other, was associated with a decreased risk of low performance, with the effect being stronger for immigrant students.

FML-Based Reinforcement Learning Agent with Fuzzy Ontology for Human-Robot Cooperative Edutainment

The currently observed developments in Artificial Intelligence (AI) and its influence on different types of industries mean that human-robot cooperation is of special importance. Various types of robots have been applied to the so-called field of Edutainment, i.e., the field that combines education with entertainment. This paper introduces a novel fuzzy-based system for a human-robot cooperative Edutainment. This co-learning system includes a brain-computer interface (BCI) ontology model and a Fuzzy Markup Language (FML)-based Reinforcement Learning Agent (FRL-Agent). The proposed FRL-Agent is composed of (1) a human learning agent, (2) a robotic teaching agent, (3) a Bayesian estimation agent, (4) a robotic BCI agent, (5) a fuzzy machine learning agent, and (6) a fuzzy BCI ontology. In order to verify the effectiveness of the proposed system, the FRL-Agent is used as a robot teacher in a number of elementary schools, junior high schools, and at a university to allow robot teachers and students to learn together in the classroom. The participated students use handheld devices to indirectly or directly interact with the robot teachers to learn English. Additionally, a number of university students wear a commercial EEG device with eight electrode channels to learn English and listen to music. In the experiments, the robotic BCI agent analyzes the collected signals from the EEG device and transforms them into five physiological indices when the students are learning or listening. The Bayesian estimation agent and fuzzy machine learning agent optimize the parameters of the FRL agent and store them in the fuzzy BCI ontology. The experimental results show that the robot teachers motivate students to learn and stimulate their progress. The fuzzy machine learning agent is able to predict the five physiological indices based on the eight-channel EEG data and the trained model. In addition, we also train the model to predict the other students’ feelings based on the analyzed physiological indices and labeled feelings. The FRL agent is able to provide personalized learning content based on the developed human and robot cooperative edutainment approaches. To our knowledge, the FRL agent has not applied to the teaching fields such as elementary schools before and it opens up a promising new line of research in human and robot co-learning. In the future, we hope the FRL agent will solve such an existing problem in the classroom that the high-performing students feel the learning contents are too simple to motivate their learning or the low-performing students are unable to keep up with the learning progress to choose to give up learning.

“Connecting online”: The structure and content of students' asynchronous online networks in a blended engineering class

Asynchronous online discussion has been widely used in higher education settings to create blended learning environments. Students form intricate social networks in asynchronous online discussions that promote help-seeking and help-providing. However, we know little about how students seek and receive help in asynchronous online discussions in blended engineering classes. This study employed a mixed-method approach by combining social network analysis and content analysis to describe students' interactions and help-seeking behaviors and to estimate their predictive power for academic performance on an asynchronous online discussion across several semesters of the same course. Social network analysis was performed to analyze the students' interactions, and content analysis was conducted to analyze the substance of their posts. The findings of this study showed variation in the structure of the social network across semesters, which is further explained by taking into account the content of the posts and the people present, both in class and online. There was a statistically significant difference in Asking for Answer Verification behavior between high-performing students and low-performing students in one semester. In addition, most of the students across all of the semesters were inclined to engage with the asynchronous online discussion by exhibiting Asking Technical Questions behavior. Based on the study findings, instructors should take on an authority role both in the classroom and on the online discussion forum itself and support students' help-seeking behaviors in asynchronous online discussions.

Educational Research Report Correlation between Student Self-Assessment and Proctor Evaluation in a Veterinary Surgical Laboratory.

Self-assessment has been shown to facilitate learning, goal setting, and professional development. We sought to evaluate whether veterinary students in a surgical curriculum would have self-assessments that differed from proctor evaluations and whether high-performing students would differ from low-performing students in self-assessment characteristics. Student and proctor assessments were compared for 8 weeks of a spay/neuter surgical laboratory taking place in the second year of the curriculum. Eight students were classified as high-performing, and 10 students were classified as low-performing. A quantitative evaluation of the scores and a qualitative assessment of written comments were completed. Proctors assigned higher scores to high-performing students compared to low-performing students, but no difference was observed overall in self-assessment scores assigned by students. When only anesthesia students were evaluated, we found a difference in self-assessment scores for high- versus low-performers, but this was not true for surgery students. Differences between proctor and student assessment scores diminished over time for all students and for anesthesia students, but not for surgery students. High-performing student anesthetists self-assessed and received proctor assessments with higher scores in technical skills. Comments from high-performing students tended to be less reflective and more positive. Low-performing students were more defensive and more likely to use I-statements in their comments. Overall, quantitative analysis did not reveal a difference in self-assessment between high-performers and low-performers; however, specific differences existed in qualitative characteristics, surgery versus anesthesia students, and proctor assessments. The differences in self-assessment between high- and low-performing students suggest areas of further investigation for the use of reflection in education.

Knowledge self-monitoring, efficiency, and determinants of self-confidence statement in multiple choice questions in medical students

BackgroundMultiple-choice question (MCQ) tests are commonly used to evaluate medical students, but they do not assess self-confidence nor penalize lucky guess or harmful behaviors. Based on a scoring method according to the appropriateness of confidence in answers, the study aimed at assessing knowledge self-monitoring and efficiency, and the determinants of self-confidence.MethodsA cross-sectional study of 842 s- and third-year medical students who were asked to state their level of confidence (A: very confident, B: moderately confident and C: not confident) during 12 tests (106,806 events). A bonus was applied if the level of confidence matched with the correctness of the answer, and a penalty was applied in the case of inappropriate confidence.ResultsLevel A was selected more appropriately by the top 20% students whereas level C was selected more appropriately by the lower 20% students. Efficiency of higher-performing students was higher when correct (among correct answers, rate of A statement), but worse when incorrect compared to the bottom 20% students (among incorrect answers, rate of C statement). B and C statements were independently associated with female and male gender, respectively (OR for male vs female = 0.89 [0.82–0.96], p = 0.004, for level B and 1.15 [1.01–1.32], p = 0.047, for level C).ConclusionWhile both addressing the gender confidence gap, knowledge self-monitoring might improve awareness of students’ knowledge whereas efficiency might evaluate appropriate behavior in clinical practice. These results suggest differential feedback during training in higher versus lower-performing students, and potentially harmful behavior in decision-making during clinical practice in higher-performing students.

The role of metacognition in the first-year design lab

Metacognition, or the ability to think about thinking, plays a significant role in the performance of first-year design students. Although the number of studies that focus on metacognition has increased in the past decade, additional studies are needed to more fully investigate metacognition and the use of metacognitive strategies in design education. Thus, this study focused on the influence of metacognitive knowledge, monitoring, and control on first-year design students’ performance. The conditions leading to changes in first-year design students’ metacognitive thinking and behaviors were also investigated. The processes of gathering data through concurrent verbalization and retrospective verbalization methods and a questionnaire are described. Thematic data analysis was used to extract the emerging themes from these data sources. Results indicated that metacognitive thinking was present in the generation and development of design ideas. Comparisons of higher- and lower-performing students demonstrated the importance of metacognitive thinking during design learning tasks; higher-performing (HP) students tended to focus more on metacognitive thinking, whereas lower-performing (LP) students focused more on cognitive activities. Other comparisons between HP and LP students, along with recommendations for improving students’ problem solving performance in design courses, are shared.