918 resultados para Predicting Student Success


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This paper explores factors that faculty perceive as significant in influencing student success in online education. Technological support, degree of comfort with technology and a student’s personal characteristics were deemed by faculty as critical to success. Understanding these key factors could help to improve student success in online education.

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This paper examines empirical studies on accountability, quality, and student success in online education. It advances that accountability and quality are critical components for student success in online education. It concludes that there is a lack of empirical studies that examine the effects of these measures on student success.

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Social media tools are increasingly popular in Computer Supported Collaborative Learning and the analysis of students' contributions on these tools is an emerging research direction. Previous studies have mainly focused on examining quantitative behavior indicators on social media tools. In contrast, the approach proposed in this paper relies on the actual content analysis of each student's contributions in a learning environment. More specifically, in this study, textual complexity analysis is applied to investigate how student's writing style on social media tools can be used to predict their academic performance and their learning style. Multiple textual complexity indices are used for analyzing the blog and microblog posts of 27 students engaged in a project-based learning activity. The preliminary results of this pilot study are encouraging, with several indexes predictive of student grades and/or learning styles.

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Abstract: Respiratory therapists must be able to care for their patients safely, efficiently and competently. They manage critically ill patients on life support systems. As a member of the anesthesia team they are responsible for the vulnerable patient undergoing surgery. Within all areas of the hospital they are called upon to make decisions and judgements concerning patient treatment. The environment that is found in the modern clinical setting is often stressful and demanding. The respiratory and anesthesia technology program has the responsibility of preparing competent practioners who graduate not only with a broad knowledge base but with the affective competencies that are required to meet these challenges. Faculty and clinical instructors in the program of Respiratory and Anesthesia Technology have been troubled by rising attrition rates and weak performance of students. It is apparent that this is not a problem unique to Vanier College. The rationale for this study was multi-fold; to establish a definition of student success, to determine whether pre-admission academic abilities can predict success in the program and whether scores on a professional behavioural aptitudes tool can predict success in the clinical year of the program. Predictors were sought that could be used either in the pre-program admission policies or during the course of study in order to ensure success throughout the program and beyond. A qualitative analysis involving clinical instructors and faculty (n=5) was carried out to explore what success signified for a student in the respiratory and anesthesia program. While this process revealed that a student who obtained a grade above 77.5% was considered “successful”, the concept surrounding success was a much more complex issue. Affective as well as cognitive and psychomotor abilities complete the model of the successful student. Appropriate behaviour and certain character traits in a respiratory therapy student are considered to be significant elements leading to success. Assessment of students in their clinical year of the respiratory & anesthesia technology program currently include little measurement of abilities in the affective domain, and the resulting grade becomes primarily a measure of academic and procedural skills. A quantitative study of preadmission records and final program grades was obtained from a single cohort of respiratory and anesthesia technology students who began the program in 2005 and graduated in 2008 (n=16). Data was collected and a descriptive analysis (analysis of variance, Pearson correlation) was used to determine the relationship between preadmission grades and success. The lack of association between the high school grades and grades in the program ran contrary to some of the findings in the literature and it can be cautiously inferred that preadmission grades do not predict success in the program. To ascertain the predictive significance of evaluating professional behavioural skills and success in clinical internship, a behaviour assessment tool was used by clinical instructors and faculty to score each student during a rotation in their third year of the program which was clinical internship. The results of this analysis showed that a moderately strong association could be made between a high score on the behavior assessment tool and final clinical grades. Therefore this tool may be effective in predicting success in the clinical year of the program. Refining the admissions process to meet the challenge and responsibility of turning out graduates who are capable of meeting the needs of the profession is difficult but essential. The capacity to predict which students possess the affective competencies necessary to cope and succeed in their clinical year is conceivably more important than their academic abilities. Although these preliminary findings contribute, to some degree, to the literature that exists concerning methods of predicting success in a respiratory and anesthesia technology program, much data is still unknown. Further quantitative and qualitative research is required using a broader population base to substantiate the findings of this small study.||Résumé: Les inhalothérapeutes doivent être capables de prodiguer des soins à leurs patients d’une manière sécuritaire, efficace et compétente. Ils/elles peuvent être appelé(e)s à gérer les soins aux personnes gravement malades branchées à un respirateur artificiel. En tant que membres de l’équipe d’anesthésie, ils/elles sont responsables des patients qui subissent une chirurgie. Ils/elles sont sollicité(e)s par tous les secteurs de l’hôpital pour décider ou juger des traitements à apporter aux malades. L’environnement dans lequel ils/elles travaillent est souvent stressant et exigeant. Le programme de Techniques d’inhalothérapie et d’anesthésie vise à former des inhalothérapeutes compétent(e)s qui possèdent non seulement les connaissances propres à la discipline mais également les aptitudes affectives nécessaires pour faire face à ces défis. Les enseignant(e)s et instructeur(e)s cliniques en Techniques d’inhalothérapie et d’anesthésie sont préoccupé(e)s par le taux d’abandon croissant et la faible performance des étudiant(e)s dans le programme. Il semble que ce problème ne soit pas unique au Collège Vanier. Le but de cette recherche est multiple : définir ce qu’est «réussir» pour les étudiant(e)s de ce programme; déterminer si les aptitudes scolaires acquises avant l’admission au programme peuvent aider à prévoir le succès des étudiant(e)s dans le programme; et si les résultats obtenus à un test mesurant les aptitudes comportementales professionnelles permettent de prévoir le succès des étudiant(e)s dans le stage clinique du programme. On a essayé d’identifier des facteurs qui pourraient être utilisés dans les politiques d’admission au programme ou celles régissant le cheminement dans le programme qui permettraient d’assurer le succès au cours du programme et par la suite. Une analyse qualitative a été conduite auprès des instructeur(e)s cliniques et des enseignant(e)s (n=5) afin d’étudier la notion de « réussite » des étudiant(e)s dans le programme. Bien qu’un(e) étudiant(e) ayant obtenu une note supérieure à 77.5% soit considéré(e) comme ayant « réussi », la notion de « réussite » est beaucoup plus complexe. Des aptitudes affectives, autant que cognitives et psychomotrices complètent le modèle d’un(e) étudiant(e) ayant réussi. Un comportement approprié et certains traits de caractère sont considérés comme des facteurs importants pour la réussite d’un(e) étudiant(e) en techniques d’inhalothérapie et d’anesthésie. L’évaluation qui se fait actuellement des étudiant(e)s dans le stage clinique du programme ne porte que peu sur les aptitudes affectives, et le résultat obtenu témoigne essentiellement des aptitudes scolaires et procédurales. Une analyse quantitative des dossiers des étudiant(e)s avant leur admission au programme et leurs notes finales a été conduite auprès d’une cohorte d’étudiant(e)s ayant commencé le programme en 2005 et gradué en 2008 (n=16). Des données ont été recueillies et une analyse descriptive (analyse de la variance, corrélation de Pearson) ont été faites afin de déterminer l’existence d’un lien entre les notes obtenues au secondaire et celles obtenues dans le programme. L’absence de corrélation entre les deux catégories de notes va à l’encontre de certaines recherches publiées et on peut déduire avec réserve que les notes obtenues avant l’admission au programme ne permettent pas de prévoir la réussite dans le programme. Afin de vérifier la portée de l’évaluation du comportement professionnel et de la réussite en milieu clinique quant à la prévision de réussite dans le programme, une méthode d’évaluation du comportement a été appliquée par les instructeurs(e) cliniques et les enseignant(e)s pour évaluer chaque étudiant(e) au cours d’une rotation dans leur troisième année de stage clinique. Les résultats de cette analyse ont démontré qu’une corrélation moyennement forte pouvait être faite entre une bonne note à l’évaluation comportementale et les notes finales du stage clinique. Perfectionner le processus d’admission au programme afin d’assumer la responsabilité de former des diplômé(e)s capables de répondre aux besoins de la profession est difficile mais essentiel. Avoir les moyens de prévoir quels/quelles étudiant(e)s ont les compétences affectives nécessaires pour faire face à la réussite de leur année de stage clinique est peut être plus important que d’avoir les aptitudes scolaires. Bien que ces observations préliminaires contribuent, à un certain degré, à la littérature existante sur les méthodes de prévoir la réussite dans le programme d’inhalothérapie et d’anesthésie, plusieurs données restent inconnues. Une recherche quantitative et qualitative plus élaborée, conduite sur un échantillon plus large de la population, est nécessaire afin de corroborer les résultats de cette étude limitée.

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While the engagement, success and retention of first year students are ongoing issues in higher education, they are currently of considerable and increasing importance as the pressures on teaching and learning from the new standards framework and performance funding intensifies. This Nuts & Bolts presentation introduces the concept of a maturity model and its application to the assessment of the capability of higher education institutions to address student engagement, success and retention. Participants will be provided with (a) a concise description of the concept and features of a maturity model; and (b) the opportunity to explore the potential application of maturity models (i) to the management of student engagement and retention programs and strategies within an institution and (ii) to the improvement of these features by benchmarking across the sector.

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Learning analytics is the analysis of static and dynamic data extracted from virtual learning environments, in order to understand and optimize the learning process. Generally, this dynamic data is generated by the interactions which take place in the virtual learning environment. At the present time, many implementations for grouping of data have been proposed, but there is no consensus yet on which interactions and groups must be measured and analyzed. There is also no agreement on what is the influence of these interactions, if any, on learning outcomes, academic performance or student success. This study presents three different extant interaction typologies in e-learning and analyzes the relation of their components with students? academic performance. The three different classifications are based on the agents involved in the learning process, the frequency of use and the participation mode, respectively. The main findings from the research are: a) that agent-based classifications offer a better explanation of student academic performance; b) that at least one component in each typology predicts academic performance; and c) that student-teacher and student-student, evaluating students, and active interactions, respectively, have a significant impact on academic performance, while the other interaction types are not significantly related to academic performance.

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This dissertation had two purposes: first, to analyze how required sequenced college preparatory courses in mathematics, reading, and writing affect students' academic success and, second, to add to a theoretical model for predicting student retention at a community college. Grade point average, number of degree credits earned, and re-enrollment rate were measured as determinants of academic success. The treatment group had a significantly higher grade point average than the control group. There was no significant difference in the number of degree credits earned or re-enrollment rate for the groups. A series of logistic regressions used the independent variables E-ASSET scores in math, reading, and writing; number of college prep areas required; credits earned; grade point average; students' status; academic restrictions/required course sequencing; sex; race; and socio-economic status to determine the predictor variables for retention. The academic variable that showed the greatest potential as a predictor for retention was grade point average. Overall, receiving financial aid was the greatest predictor for re-enrollment. For a financial aid recipient the odds of re-enrollment were 2.70 times more likely than if no financial aid was received.

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This dissertation had two purposes: first, to analyze how required sequenced college preparatory courses in mathematics, reading, and writing affect students' academic success and, second, to add to a theoretical model for predicting student retention at a community college. Grade point average, number of degree credits earned, and reenrollment rate were measured as determinants of academic success. The treatment group had a significantly higher grade point average than the control group. There was no significant difference in the number of degree credits earned or re-enrollment rate for the groups. A series of logistic regressions used the independent variables E-ASSET scores in math, reading, and writing; number of college prep areas required; credits earned; grade point average; students' status; academic restrictions/required course sequencing; sex; race; and socio-economic status to determine the predictor variables for retention. The academic variable that showed the greatest potential as a predictor for retention was grade point average. Overall, receiving financial aid was the greatest predictor for reenrollment. For a financial aid recipient the odds of reenrollment were 2.70 times more likely than if no financial aid was received.

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For the past several years, U.S. colleges and universities have faced increased pressure to improve retention and graduation rates. At the same time, educational institutions have placed a greater emphasis on the importance of enrolling more students in STEM (science, technology, engineering and mathematics) programs and producing more STEM graduates. The resulting problem faced by educators involves finding new ways to support the success of STEM majors, regardless of their pre-college academic preparation. The purpose of my research study involved utilizing first-year STEM majors’ math SAT scores, unweighted high school GPA, math placement test scores, and the highest level of math taken in high school to develop models for predicting those who were likely to pass their first math and science courses. In doing so, the study aimed to provide a strategy to address the challenge of improving the passing rates of those first-year students attempting STEM-related courses. The study sample included 1018 first-year STEM majors who had entered the same large, public, urban, Hispanic-serving, research university in the Southeastern U.S. between 2010 and 2012. The research design involved the use of hierarchical logistic regression to determine the significance of utilizing the four independent variables to develop models for predicting success in math and science. The resulting data indicated that the overall model of predictors (which included all four predictor variables) was statistically significant for predicting those students who passed their first math course and for predicting those students who passed their first science course. Individually, all four predictor variables were found to be statistically significant for predicting those who had passed math, with the unweighted high school GPA and the highest math taken in high school accounting for the largest amount of unique variance. Those two variables also improved the regression model’s percentage of correctly predicting that dependent variable. The only variable that was found to be statistically significant for predicting those who had passed science was the students’ unweighted high school GPA. Overall, the results of my study have been offered as my contribution to the literature on predicting first-year student success, especially within the STEM disciplines.

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There is widespread recognition that higher education institutions (HEIs) must actively support commencing students to ensure equity in access to the opportunities afforded by higher education. This role is particularly critical for students who because of educational, cultural or financial disadvantage or because they are members of social groups currently under-represented in higher education, may require additional transitional support to “level the playing field.” The challenge faced by HEIs is to provide this “support” in a way that is integrated into regular teaching and learning practices and reaches all commencing students. The Student Success Program (SSP) is an intervention in operation at the Queensland University of Technology (QUT) designed to identify and support those students deemed to be at risk of disengaging from their learning and their institution. Two sets of evidence of the impact of the SSP are presented: First, its expansion (a) from a one-faculty pilot project (Nelson, Duncan & Clarke, 2009) to all faculties and (b) into a variety of applications mirroring the student life cycle; and second, an evaluation of the impact of the SSP on students exposed to it. The outcomes suggest that: the SSP is an example of good practice that can be successfully applied to a variety of learning contexts and student enrolment situations; and the impact of the intervention on student persistence is sustained for at least 12 months and positively influences student retention. It is claimed that the good practice evidenced by the SSP is dependent on its integration into the broader First Year Experience Program at QUT as an example of transition pedagogy in action.

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As higher education institutions respond to government targets to widen participation, their student populations will become increasingly diverse, and the issues around student success and retention will be more closely scrutinised. The concept of student engagement is a key factor in student achievement and retention and Australasian institutions have a range of initiatives aimed at monitoring and intervening with students who are at risk of disengaging. Within the widening participation agenda, it is absolutely critical that these initiatives are designed to enable success for all students, particularly those for whom social and cultural disadvantage have been a barrier. Consequently, for the sector, initiatives of this type must be consistent with the concept of social justice and a set of principles would provide this foundation. This session will provide an opportunity for participants to examine a draft set of principles and to discuss their potential value for the participants’ institutional contexts.

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An identified issue within higher education is the high rates of student attrition after the first year, especially in the STEM disciplines. To address this issue, it is essential to reexamine and redesign the first year curriculum to engage and retain the students' interests while also scaffolding their learning experience. This session reports on an initiative based on the principles of the “inverted curriculum” within the Bachelor of Technology (BIT) course at the Queensland University of Technology (QUT) that began in 2009 and has resulted in a reduction in first-year attrition rates from 18% in 2008 to 10% in 2009 and 2010 despite a growth in student intake of 15% to 40% in the past two years. We present the process and methods that helped achieve this and initiate a discussion on the innovations that are possible within this concept of inverted curriculum and how it can be implemented.

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Graphical tasks have become a prominent aspect of mathematics assessment. From a conceptual stance, the purpose of this study was to better understand the composition of graphical tasks commonly used to assess students’ mathematics understandings. Through an iterative design, the investigation described the sense making of 11–12-year-olds as they decoded mathematics tasks which contained a graphic. An ongoing analysis of two phases of data collection was undertaken as we analysed the extent to which various elements of text, graphics, and symbols influenced student sense making. Specifically, the study outlined the changed behaviour (and performance) of the participants as they solved graphical tasks that had been modified with respect to these elements. We propose a theoretical framework for understanding the composition of a graphical task and identify three specific elements which are dependently and independently related to each other, namely: the graphic; the text; and the symbols. Results indicated that although changes to the graphical tasks were minimal, a change in student success and understanding was most evident when the graphic element was modified. Implications include the need for test designers to carefully consider the graphics embedded within mathematics tasks since the elements within graphical tasks greatly influence student understanding.

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Analysing the engagement of students in university-based Facebook groups can shed light on the nature of their learning experience and highlight leverage points to build on student success. While post-semester surveys and demographic participation data can highlight who was involved and how they subsequently felt about the experience, these techniques do not necessarily reflect real-time engagement. One way to gain insight into in-situ student experiences is by categorising the original posts and comments into predetermined frameworks of learning. This paper offers a systematic method of coding Facebook contributions within various engagement categories: motivation, discourse, cognition and emotive responses.

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First year medical laboratory science students (up to 120) undertake a group e-poster project, based in a blended learning model Google Drive, encompassing Google’s cloud computing software, provides a readily accessible, transparent online space for students to collaborate with each other and realise tangible outcomes from their learning The Cube provides an inspiring digital learning display space for student ‘conference style’ presentations