Predicting Academic Performance: A Systematic Literature Review

The ability to predict student performance in a course or program creates opportunities to improve educational outcomes. With effective performance prediction approaches, instructors can allocate resources and instruction more accurately. Research in this area seeks to identify features that can be used to make predictions, to identify algorithms that can improve predictions, and to quantify aspects of student performance. Moreover, research in predicting student performance seeks to determine interrelated features and to identify the underlying reasons why certain features work better than others. This working group report presents a systematic literature review of work in the area of predicting student performance. Our analysis shows a clearly increasing amount of research in this area, as well as an increasing variety of techniques used. At the same time, the review uncovered a number of issues with research quality that drives a need for the community to provide more detailed reporting of methods and results and to increase efforts to validate and replicate work.Peer reviewe

Capturing doping attitudes by self-report declarations and implicit assessment: a methodology study

BACKGROUND: Understanding athletes' attitudes and behavioural intentions towards performance enhancement is critical to informing anti-doping intervention strategies. Capturing the complexity of these attitudes beyond verbal declarations requires indirect methods. This pilot study was aimed at developing and validating a method to assess implicit doping attitudes using an Implicit Associations Test (IAT) approach. METHODS: The conventional IAT evaluation task (categorising 'good' and 'bad' words) was combined with a novel 'doping' versus 'nutrition supplements' category pair to create a performance-enhancement related IAT protocol (PE-IAT). The difference between average response times to 'good-doping' and 'bad-doping' combinations represents an estimate of implicit attitude towards doping in relation to nutritional supplements. 111 sports and exercise science undergraduates completed the PE-IAT, the Performance Enhancement Attitude Scale (PEAS) and answered questions regarding their beliefs about doping. RESULTS: Longer response times were observed in the mixed category discrimination trials where categories 'good' and 'doping' shared the same response key (compared to 'bad-doping' combination on the same key) indicating a less favourable evaluation of doping substances. The PE-IAT measure did not correlate significantly with the declared doping attitudes (r = .181, p = .142), indicating a predictable partial dissociation. Action-oriented self-report expressed stronger associations with PE-IAT: participants who declared they would consider using doping showed significantly less implicit negativity towards banned substances (U = 109.00, p = .047). Similarly, those who reported more lenient explicit attitudes towards doping or expressly supported legalizing it, showed less implicit negativity towards doping in the sample, although neither observed differences reached statistical significance (t = 1.300, p = .198, and U = 231.00, p = .319, respectively). Known-group validation strategy yielded mixed results: while competitive sport participants scored significantly lower than non-competitive ones on the PEAS (t = -2.71, p = .008), the two groups did not differ on PE-IAT (t = -.093, p = .926). CONCLUSION: The results suggest a potential of the PE-IAT method to capture undeclared attitudes to doping and predict behaviour, which can support targeted anti-doping intervention and related research. The initial evidence of validity is promising but also indicates a need for improvement to the protocol and stimulus material

Research and Education in Computational Science and Engineering

Over the past two decades the field of computational science and engineering (CSE) has penetrated both basic and applied research in academia, industry, and laboratories to advance discovery, optimize systems, support decision-makers, and educate the scientific and engineering workforce. Informed by centuries of theory and experiment, CSE performs computational experiments to answer questions that neither theory nor experiment alone is equipped to answer. CSE provides scientists and engineers of all persuasions with algorithmic inventions and software systems that transcend disciplines and scales. Carried on a wave of digital technology, CSE brings the power of parallelism to bear on troves of data. Mathematics-based advanced computing has become a prevalent means of discovery and innovation in essentially all areas of science, engineering, technology, and society; and the CSE community is at the core of this transformation. However, a combination of disruptive developments---including the architectural complexity of extreme-scale computing, the data revolution that engulfs the planet, and the specialization required to follow the applications to new frontiers---is redefining the scope and reach of the CSE endeavor. This report describes the rapid expansion of CSE and the challenges to sustaining its bold advances. The report also presents strategies and directions for CSE research and education for the next decade.Comment: Major revision, to appear in SIAM Revie

ProPelled: The Effects of Grants on Graduation, Earnings, and Welfare

We estimate the effect of grant aid on poor college students’ attainment and earnings using student-level administrative data from four-year public colleges in Texas. To identify these effects, we exploit a discontinuity in grant generosity as a function of family income. Eligibility for the maximum Pell Grant significantly increases degree receipt and earnings beginning four years after entry. Within 10 years, imputed taxes on eligible students’ earnings gains fully recoup total government expenditures generated by initial eligibility. To clarify how these estimates relate to social welfare, we develop a general theoretical model and derive sufficient statistics for the welfare implications of changes in the price of college. Whether additional grant aid increases welfare depends on (1) net externalities from recipients’ behavioral responses and (2) a direct effect of mitigating credit constraints or other frictions that inflate students’ in-school marginal utility. Calibrating our model using nationally representative consumption data suggests that increasing grant aid for the average college student by $1 could generate negative externalities as high as$0.50 and still improve welfare. Applying our welfare formula and estimated direct effects to our setting and others suggests considerable welfare gains from grants that target low-income students

2016 Annual Report of the Graduate School of Engineering and Management, Air Force Institute of Technology

The Graduate School\u27s Annual Report highlights research focus areas, new academic programs, faculty accomplishments and news, and provides top-level sponsor-funded research data and information

The impact of emotions on student participation in an assessed, online, collaborative activity

There is growing recognition of the importance of emotions in academic online learning contexts. However, there is still little known about the role of emotions in social and collaborative online learning settings, especially the relationship between emotions and student participation. To explore this relationship, this study used a prospective longitudinal research design to follow 46 distance learning students throughout a 3-week assessed, online, collaborative activity. This approach allowed the fluctuating and dynamic aspects of emotions to be explored as well as the relationship between emotions and student participation in the collaborative activity. Self-report data were gathered using a semistructured online diary at five time points throughout the task (once at the start of the collaborative activity, three times during the activity, and the final entry after the activity had finished). Findings revealed that learners generally perceived pleasant emotions (such as relief, satisfaction and enjoyment) to have positive impacts, or no impact, on participation, whereas unpleasant emotions (such as anxiety, frustration, and disappointment) were generally perceived to have negative impacts, or no impact, on participation. Interestingly, however, anxiety, and to a smaller extent frustration, were perceived by a number of students to have positive impacts during the activity. To conclude this paper, implications for educators are highlighted

METODOLOGIAS ATIVAS NO ENSINO SUPERIOR: UM MAPEAMENTO SISTEMÁTICO NO CONTEXTO DOS CURSOS DE ENGENHARIA

Active learning is all pedagogical alternatives that place the focus of learning on the students. With the mediation of competent teachers, the students learn by discovery, by investigation, and by problems. Such methodologies commonly promote more content retention and comprehension once the students are engaged in activities, whether through research, group collaborations, discussion, and problem solving. This work aimed to verify the temporal evolution of active learning methods in higher education Engineering courses, based on a systematic mapping of the literature. We observed which are the main researchers in this field, their geographic location and which methodologies are preferred in the context of these courses. From the results, we observe a growth of scientific publications on active learning methodologies and Engineering Education, especially in the last five years of the period analysed (between 2015 and 2020). We also see researchs on this field in all continents, with a predominance of studies led by American and European researchers. In the mapped studies, the inverted classroom and problem-based learning were the most identified methodologies. It demonstrates a concern of teachers in this area to promote activities with high involvement, which allow the development of personal and professional skills and competencies, even during their training period.Las metodologías activas pueden entenderse como alternativas pedagógicas que ponen el foco del aprendizaje en los alumnos. Con la mediación de profesores competentes, los alumnos aprenden a partir del descubrimiento, la investigación y los problemas. Estas metodologías suelen promover una mayor retención y comprensión de los contenidos enseñados, ya que el alumno participa en actividades, ya sea a través de la investigación, la colaboración en grupo, el debate y la resolución de problemas. Este trabajo tuvo como objetivo verificar la evolución temporal del uso de las metodologías activas en el contexto de los cursos de educación superior en Ingeniería, a partir de un mapeo sistemático de la literatura. A partir de un protocolo de investigación debidamente definido, se buscó verificar cuáles son los principales investigadores en esta área, su ubicación geográfica y cuáles son las metodologías preferidas en el contexto de estos cursos. A partir de los resultados, se pudo observar que el crecimiento en el número de publicaciones científicas sobre metodologías activas en el contexto de la Enseñanza de la Ingeniería, especialmente en los últimos cinco años del período analizado (entre 2015 y 2020). Se puede observar la realización de investigaciones en este contexto en todos los continentes, con un predominio de estudios dirigidos por investigadores americanos y europeos. En los estudios mapeados, el flipped classroom y el aprendizaje basado en problemas fueron las metodologías más identificadas. Esto demuestra una mayor preocupación entre los profesores de la zona por promover actividades con alta implicación que permitan el desarrollo de habilidades y competencias personales y profesionales durante el periodo de formación.As metodologias ativas podem ser entendidas como alternativas pedagógicas que colocam o foco do aprendizado nos estudantes. Com mediação de docentes competentes, os alunos aprendem a partir da descoberta, da investigação e por problemas. Tais metodologias comumente promovem uma maior retenção e compreensão de contéudos ensinados, uma vez que o aprendiz se encontra engajado nas atividades, seja por meio de pesquisa, colaborações em grupo, discussão e resolução de problemas. Este trabalho teve como objetivo verificar a evolução temporal do uso de metodologias ativas, no contexto dos cursos superiores de Engenharia, a partir de um mapeamento sistemático da literatura. A partir de um protocolo de pesquisa devidamente definido, buscou-se verificar quais os principais pesquisadores desta área, sua localização geográfica e quais as metodologias preferidas no contexto destes cursos. A partir dos resultados, foi possível observar que o crescimento do número de publicações científicas sobre metodologias ativas no contexto da Educação em Engenharia, em especial nos últimos cinco anos do período analisado (entre 2015 e 2020). Pode-se notar a realização de pesquisas neste contexto em todos os continentes, com predomínio de estudos liderados por pesquisadores americanos e europeus. Nos estudos mapeados, a sala de aula invertida e a aprendizagem baseada em problemas foram as metodologias mais identificadas. Isso demostra uma maior preocupação dos professores da área em promover atividades com elevado envolvimento, que permitam o desenvolvimento de habilidades e competências pessoais e profissionais, ainda no período de formação

A Logistic Regression Study of How Pre-Enrollment Factors Predict Graduation at a Christian Historically Black University

The purpose of this logistic regression study is to review the pre-admission factors through the lenses of multiple retention constructs and graduation rates at a Christian, Historically Black College or University (HBCU). A binary logistic regression is used to analyze the odds of graduation based on a set of pre-admission factors of first-time freshmen, as predictor variables. In particular, the predictor variables of interest are eligibility of academic support based on academic scholarships, gender, international status, and type of high school attended. The outcome variable of interest is graduation. This study is important because it contributes to the scholarship in the study of Christian HBCUs and the understanding of how preadmission factors may affect graduation. This study addresses the problem by using regression relationships to guide supportive programs that reinforce retention, persistence, and completion of students based on pre-admission factors, as reflected in the work of Tinto, Astin and other theorists. The number of participants used for this regression analysis supports adequate statistical power for a medium effect size. This study took place at a Christian HBCU in north Alabama with data collected from the admissions office for the freshmen class of 2011, where N=364. The results of this study suggest that students that attend a private high school have high odds of completing a post-secondary degree at a Christian HBCU and makes recommendations to support the retention and recruitment of the targeted population. The implications for further research could include a variety of replication studies with additional preadmission factors, longitudinal, mixed methods, or qualitative studies reviewing persistence, completion, and yearly graduation rates as they relate to the preadmission factors

Considering Racial/Ethnic Diversity Experience as a Predictor of Success for Graduate Social Work Students

Social workers require a unique set of skills, knowledge and values in preparation to work with diverse populations. Graduate social work programs struggle with identifying useful admissions criteria beyond undergraduate GPA. Literature on college diversity has shown that students who have exposure to others who are different from themselves experience enhanced critical thinking skills and strong pluralistic orientation outcomes. As admission decisions are critical to shaping the profession of social work, this study considers students’ college diversity experiences as a predictor of their success in an MSW program. Three multiple regression analyses looking at overall field competency scores (F (13, 545), p < .01), MSW GPA for graduates (F (13, 391), p < .001), and MSW GPA for current students (F (13, 139), p < .001) found that advanced standing status, gender, undergraduate GPA, full-time experience, GRE scores and campus ethnic diversity scores were statistically significant predictors. Additionally two logistic regression analyses looking at critical thinking field scores (χ2(13)= 30.750, p < .05) and field scores in human rights and social justice (χ2(13)= 26.041, p < .05) found that advanced standing status, gender, undergraduate GPA, and full-time experience were statistically significant predictors. A qualitative analysis of five interviews with successful MSW students was also conducted. Undergraduate diversity experiences were present for each student but were under-emphasized for the outcomes of interest. Instead pivotal experiences with injustice both early in life and in college and identification as part of a marginalized group lead to skill and interest development in social work as well as an overall social justice orientation. Success of students identifying as marginalized, in part, was based on access to communities and groups from which they received support, hope, and a sense of belonging. The study is preliminary and associative, and thus does not allow for causal conclusions and is of only one discipline at one graduate program. Future research is suggested on the advanced standing program within social work education as well as critical mass for marginalized students. For practitioners, it is recommended that exposure and interaction with diversity be considered as an additional criterion for graduate social work admissions decisions along with traditionally considered criteria of undergraduate GPA and full-time work related experience. This study looks at different criteria for social work admissions as well as uncovers important student characteristics that help us understand their success in social work graduate studies.Educational Psychology, Department o