Analysis Of Student Performance Research Articles

An analysis of student performance with podcasting and active learning in a pharmacotherapy module

ObjectivesThe objective was to determine the effect of podcasting, with resultant increased in-class active learning time, on student performance. MethodsIn an effort to increase in-class active learning time and improve understanding of the material in a third-year pharmacotherapy course, podcasts were developed to cover specific topics and were made available outside-of-class for students in 2010. Students in the same course in the year 2009 had received identical in-class didactic instruction for these topics. End-of-course exam scores were adjusted using analysis of covariance and compared using the t-test. ResultsThe class averages on the end-of-course exams were significantly higher at 77.5 ± 1.2 (n = 65) for the class of 2009 compared to 72.9 ± 1.5 (n = 71) for the class of 2010 (p = 0.019). This difference remained significant after adjusting the 2009 and 2010 classes for the covariates. The difference between the classes was further magnified when using the covariate of GPA, 78.3 ± 1.2 compared to 72.2 ± 1.1 (p < 0.001) for the classes of 2009 and 2010, respectively. Rank ordering resulted in a significant difference in the exam grade in the lower 50th percentile 73.2 ± 1.6 (n = 34, 2009 class) compared to 65.8 ± 1.9 (n = 34, 2010 class), p = 0.004. No significant differences were noted between the two classes for those students in the upper 50th percentile. ConclusionIncreased in-class active learning time led to decreased examination scores for the lower 50th percentile of students in the 2010 cohort. One potential explanation is that students were not held accountable for completing the out-of-class preparatory exercises.

Teachers' Instructional Use of Summative Student Assessment Data

This study examines the extent to which classroom teachers self-report using summative assessment data in formative ways to shape instruction. A Web-based survey was administered to elementary, middle, and high school teachers in a large, suburban school district in central Virginia. Teachers reported administering a variety of summative assessments with varying frequency, and analyzing data at the aggregate level, most often using central tendency statistics. Useful methods for disaggregating data by content standards or student subgroups were not as frequently reported. Regardless of the methods of data analysis, a majority of teachers reported using assessment results to evaluate their instructional practice and make adjustments to support student learning. The results suggest, however, that teachers engaged in a cursory analysis of student performance fairly regularly but conduct more in-depth analyses less often. The study raises questions about how teachers can effectively use summative data for instructional purposes.

An Analysis of Students Performance Using Genetic Algorithm

Genetic algorithm plays a significant role, as search techniques for handling complex spaces, in many fields such as artificial intelligence, engineering, robotic, etc. The genetic processes on the natural evolution principles of populations have been fairly successful at solving problems and produce optimized solution from generation to generation. This is applied in students’ quantitative data analysis to identify the most impact factor in their performance in their curriculum. The results will help the educational institutions to improve the quality of teaching after evaluating the marks achieved by the students’ in academic career. This student analysis model considers the quantitative factors such as theoretical, mathematical, practical, departmental and other departmental marks to find the most impacting factor using genetic algorithm.

A Decision Tree Algorithm Pertaining to the Student Performance Analysis and Prediction

of an educational institute can be measured in terms of successful students of the institute. The analysis related to the prediction of students academic performance in higher education seems an essential requirement for the improvement in quality education. Data mining techniques play an important role in data analysis. For the construction of a classification model which could predict performance of students, particularly for engineering branches, a decision tree algorithm associated with the data mining techniques have been used in the research. A number of factors may affect the performance of students. Here some significant factors have been considered while constructing the decision tree for classifying students according to their attributes (grades). In this paper four different decision tree algorithms J48, NBtree, Reptree and Simple cart were compared and J48 decision tree algorithm is found to be the best suitable algorithm for model construction. Cross validation method and percentage split method were used to evaluate the efficiency of the different algorithms. The traditional KDD process has been used as a methodology. The WEKA (Waikato Environment for Knowledge Analysis) tool was used for analysis and prediction. . Results obtained in the present study may be helpful for identifying the weak students so that management could take appropriate actions, and success rate of students could be increased sufficiently.

Oxford-Style Debates in a Microbiology Course for Majors: A Method for Delivering Content and Engaging Critical Thinking Skills

Developing scientific expertise in the classroom involves promoting higher-order cognitive skills as well as content mastery. Effective use of constructivism can facilitate these outcomes. However this is often difficult to accomplish when delivery of content is paramount. Utilizing many of the tenets of constructivist pedagogy, we have designed an Oxford-style debate assignment to be used in an introductory microbiology course. Two teams of students were assigned a debatable topic within microbiology. Over a five-week period students completed an informative web page consisting of three parts: background on the topic, data-based positions for each side of the argument, and a data-based persuasive argument to support their assigned position. This was followed by an in-class presentation and debate. Analysis of student performance on knowledge-based questions shows that students retain debate-derived content acquired primarily outside of lectures significantly better than content delivered during a normal lecture. Importantly, students who performed poorly on the lecture-derived questions did as well on debate-derived questions as other students. Students also performed well on questions requiring higher-order cognitive skills and in synthesizing data-driven arguments in support of a position during the debate. Student perceptions of their knowledge-base in areas covered by the debate and their skills in using scientific databases and analyzing primary literature showed a significant increase in pre- and postassignment comparisons. Our data demonstrate that an Oxford-style debate can be used effectively to deliver relevant content, increase higher-order cognitive skills, and increase self-efficacy in science-specific skills, all contributing to developing expertise in the field.

Factors in the development of higher levels of reading literacy: Argumentation skills in educational practice

The highest levels of reading literacy, as defined within PISA study, include the ability to use various cognitive skills, with argumentative skills being one of the most important among them. In the present study our goal was to reveal some of the factors that influence the development of argumentative skills in Serbian schools. We investigated the extent to which argumentative skills are required in PISA reading literacy tasks, as well as the specific difficulties our students have faced on these tasks, through an analysis of student performance. We also conducted an analysis of the educational practice - by doing in-depth interviews with teachers and content analysis of students' textbooks. The results revealed that: 1) Argumentations skills are an important requirement within PISA tasks; 2) Serbian students are mostly successful at basic tasks of recognizing arguments or providing arguments for the given position; they face difficulties answering the tasks which require precise formulation of relevant arguments as well as those demanding meta-cognitive skills (e.g. recognizing persuasive strategies in the given text). Their performance is particularly poor on tasks requiring the combination of information from different sources or information presented in different formats (text, tables, or graphs); 3) There is a significant gap between the requirements for argumentation skills our students usually encounter and PISA reading literacy tasks. In this paper we discuss some of the difficulties and obstacles to encouraging the development of argumentative thinking.

Proficiência em matemática: analise do desempenho em escolas públicas estaduais de Araraquara no SARESP

The objective of this study is to present an analysis of students performance in public schools of Araraquara in relation to the proficiency in mathematics, addressing the Sistema de Avaliacao de Rendimento Escolar do Estado de Sao Paulo (SARESP), which is an important tool for support the Secretaria Estadual da Educacao in definitions focused on educational policies. To perform the analysis of students performance were considered notes in math tests, achieved by students from the third grade of high school in eleven state public schools of Araraquara. To achieve the proposed objective, were used data from SARESP for the period between 200S and 2011, made available by the State Secretariat of Education (SEE). The results showed that students in the third grade of high school of public schools in Araraquara are in the worst le\'els of proficiency in mathematics considered by SARESP. This result demonstr'ates an urgent need to seek explanations and ways to overcome this situation.

An evaluation of an exploratory intervention to improve progression in a first-year accounting course

South African universities face pressure to increase the throughput of accounting students, with a special emphasis on expanding the number of female and black graduates. To improve the progression of at-risk first-year second-semester accounting students, an intervention known as JumpStart was implemented at the Faculty of Commerce at the University of Cape Town (UCT) in 2010. JumpStart involved the allocation of skilled instructors, additional workshops, student mentors and a study skills course, thus employing a wide range of factors known to influence student success: academic, psychological and social. The intervention was evaluated using analyses of student academic performance and responses to a programme evaluation. In 2008 and 2009, only 23% and 29% of at-risk students performed well enough to progress to second-year accounting. By contrast, in 2010, 71% of JumpStart students were eligible to progress. For each gender and ethnic category, progression rates for JumpStart students were superior to those for non-JumpStart students, with the most significant improvements being made by female students and white students. An unexpected finding was a significant improvement in the progression rates of non-JumpStart at-risk students when compared with previous years, which may be at least partially explained by the weakest at-risk students choosing to join JumpStart. The responses to the programme evaluation indicated that students valued the allocation of skilled instructors and the provision of additional workshops above the other components of the intervention. A considerable difference existed between the way in which black and white students valued the study skills course and the mentor groups, with black students valuing these components of the intervention much more.

Which form of assessment provides the best information about student performance in chemistry examinations?

Background This study developed from observations of apparent achievement differences between male and female chemistry performances in a state university entrance examination. Male students performed more strongly than female students, especially in higher scores. Apart from the gender of the students, two other important factors that might influence student performance were format of questions (short-answer or multiple-choice) and type of questions (recall or application). Purpose The research question addressed in this study was: Is there a relationship between performance in state university entrance examinations in chemistry and school chemistry examinations and student gender, format of questions – multiple-choice or short-answer, and conceptual level – recall or application? Sample The two sources of data were: (1) secondary analyses of five consecutive years’ data published by the examining authority of chemistry examinations, and (2) tests conducted with 192 students which provided information about all aspects of the three variables (question format, question type and gender) under consideration. Design and methods Both sources of data were analysed using ANOVA to compare means for the variables under consideration and the statistical significance of any differences. The data from the tests were also analysed using Rasch analysis to determine differences in gender performance. Results When overall mean data are considered, both male and female students performed better on multiple-choice questions and recall questions than on short-answer questions and application questions, respectively. When overall mean data are considered, male students outperformed female students in both the university entrance and school tests, particularly in the higher scores. When data were analysed with Rasch, there was no statistically significant difference in performance between males and females of equal ability. Conclusions Both male and female students generally perform better on multiple-choice questions than they do on short-answer questions. However, when the questions are matched in terms of difficulty (using Rasch analysis), the differences in performance between multiple-choice and short-answer are quite small. Rasch analysis showed that there was little difference in performance between males and females of equal ability. This study shows that a simple face-value score analysis of relative student performance – in this case, in chemistry – can be deceptive unless the actual abilities of the students concerned, as measured by a tool such as Rasch, are taken into consideration before reaching any conclusion.

Web-based Tutorials and Traditional Face-to-Face Lectures: A Comparative Analysis of Student Performance

The authors present the results of a study conducted at a historically Black institution that compares student performance using Web-based tutorials to that of the traditional face-to-face lectures. A casual-comparative design was chosen for this study to examine the effects of instructional delivery on student performance in a business communications course with specific emphasis on the grammar and mechanics unit of study. The study spanned 4 years, beginning fall 2008 through spring 2012. Participants included 375 declared business majors who were self-enrolled in various sections of the Business Communications course during the study. The results of this study mirrored those of previous works reporting that Web-based tutorials are as effective as traditional face-to-face lecturing with regard to student performance.

Analysis of Student Performance in Large-Enrollment Life Science Courses

This study examined the historical performance of students at Michigan State University in 12 life sciences courses over 13 yr to find variables impacting student success. Hierarchical linear modeling predicted 25.0–62.8% of the variance in students’ grades in the courses analyzed. The primary predictor of a student's course grade was his or her entering grade point average; except for the second course in a series (i.e., Biochemistry II), in which the grade for the first course in the series (i.e., Biochemistry I) was often the best predictor, as judged by β values. Student gender and major were also statistically significant for a majority of the courses studied. Female students averaged grades 0.067–0.303 lower than their equivalent male counterparts, and majors averaged grades were 0.088–0.397 higher than nonmajors. Grades earned in prerequisite courses provided minimal predictive ability. Ethnicity and involvements in honors college or science residential college were generally insignificant.

A General Multivariate Latent Growth Model With Applications to Student Achievement

The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context, the analysis of student performance and capabilities plays a fundamental role. In this work, the authors propose a multivariate latent growth model for studying the performances of a cohort of students of the University of Bologna. The model proposed is innovative since it is composed by (a) multivariate growth models that allow the capture of different dynamics of student performance indicators over time and (b) a factor model that allows measurement of the general latent student capability. The flexibility of the model proposed allows its applications in several fields such as socioeconomic settings in which personal behaviors are studied using panel data.

Ubiquitous tutoring in laboratories based on wireless sensor networks

Industrial education places a high premium on experiences in practical hands-on training, though it is commonly recognized for the deprivation in its opportunities of student performance analysis due to lack of recorded data as such. In the present study, the technology of wireless sensor networks has been implemented in the tutoring in courses offered in laboratory skills, where the students’ experimental skills and learning inclinations have been examined. Two sets of questionnaires in the respective aspects have been developed to be administered in order to have pretest–posttest scores obtained. As illustrated in the results derived from the study, a learning environment where wireless sensor networks provide a significant degree of support during laboratory sessions, student performance had significantly improved, and this has been proven evidently for the students in the low-achievement group when being compared to the results delivered by the students in the high-achievement group.

Managing women with acute physiological deterioration: Student midwives performance in a simulated setting

Midwives' ability to manage maternal deterioration and 'failure to rescue' are of concern with questions over knowledge, clinical skills and the implications for maternal morbidity and, mortality rates. In a simulated setting our objective was to assess student midwives' ability to assess, and manage maternal deterioration using measures of knowledge, situation awareness and skill, performance. An exploratory quantitative analysis of student performance based upon performance, ratings derived from knowledge tests and observational ratings. During 2010 thirty-five student, midwives attended a simulation laboratory completing a knowledge questionnaire and two video, recorded simulated scenarios. Patient actresses wearing a 'birthing suit' simulated deteriorating, women with post-partum and ante-partum haemorrhage (PPH and APH). Situation awareness was, measured at the end of each scenario. Applicable descriptive and inferential statistical tests were, applied to the data. The mean total knowledge score was 75% (range 46-91%) with low skill performance, means for both scenarios 54% (range 39-70%). There was no difference in performance between the scenarios, however performance of key observations decreased as the women deteriorated; with significant reductions in key vital signs such as blood pressure and blood loss measurements. Situation, awareness scores were also low (54%) with awareness decreasing significantly (t(32)=2.247, p=0.032), in the second and more difficult APH scenario. Whilst knowledge levels were generally good, skills were generally poor and decreased as the women deteriorated. Such failures to apply knowledge in emergency stressful situations may be resolved by repetitive high stakes and high fidelity simulation.

Meta clusters through minimum spanning tree based clustering for performance analysis of students

Clustering is a process of discovering group of objects such that the objects of the same group are similar, and objects belonging to different groups are dissimilar. A number of clustering algorithms exist that can solve the problem of clustering, but most of them are very sensitive to their input parameters. Minimum Spanning Tree based clustering algorithm is capable of detecting clusters with irregular boundaries. In this paper we propose Minimum Spanning Tree based clustering algorithm to find Meta clusters (cluster of clusters). The algorithm uses a new cluster validation criterion based on the geometric property of data partition of the data set in order to find the proper number of clusters at each level. The algorithm works in two phases. The first phase of the algorithm create clusters with guaranteed intra-cluster similarity, where as the second phase of the algorithm create dendrogram using the clusters as objects with guaranteed inter-cluster similarity. In this paper we presented experimental result on some synthetic data sets namely student semester mark. Experimental result shows that the proposed algorithm performs better than K-means algorithm. The first phase of the algorithm uses divisive approach, where as the second phase uses agglomerative approach. In this paper we used both the approaches to analyze the performance of the students.

Analysis of Student Performance on Multiple-Choice Questions in General Chemistry

The percentage of students choosing the correct answer (PSCA) on 17 multiple-choice algorithmic questions taken from general chemistry exams is analyzed. PSCAs for these questions varied from 47 to 93%, and a decrease of 4.5% in PSCA was observed with each additional step in the algorithm required for solving the problem (R2 = 0.80). Variants of a subset of these questions were also examined and reveal the effect of making changes to a particular algorithmic question on the ability of students to choose the correct answer.

University of Florida College of Medicine

University of Florida College of Medicine

Teaching Introductory Geographic Information Systems through Problem-based Learning and Public Scholarship

Teaching geographic information systems (GIS) requires linking concepts with technical skills, which can be challenging, especially in standard lecture and laboratory-format courses. This paper reports on an introductory undergraduate GIS course that incorporated a community-driven problem-based learning exercise as a major component of the course. Analysis of student performance and course evaluations indicates that the exercise was effective in aiding student learning of GIS, while also teaching research and other professional development skills, and providing insight into an important social issue within their community. Benefits and cautions are discussed from the perspective of students, instructor, university and local community.

The Evolution of a Testing Tool for Measuring Undergraduate Information Literacy Skills in the Online Environment

The construction and validity of an assessment tool mapped to objectives in a high enrollment credit-bearing information literacy course delivered primarily online is the focus of this article. An open book and non-proctored objective test can be a reliable measure for assessing student competencies in basic information literacy skills, both at the course level and for reporting to national accrediting bodies and state agencies. An analysis of overall student performance on test items that are mapped to information literacy outcomes helps to identify competencies that need improvement in a course, as well as provide a baseline for informing the process of assessing student learning outcomes in an undergraduate curriculum.

Video Analysis of Athletic Training Student Performance: Changing Educational Competency into Clinical Proficiency

Context: Assessing clinical proficiency and documenting learning over time is quite challenging. Educators must look for unique ways to effectively examine students' performance and archive evidence of their academic progress. Objective: To discuss the use of video analysis to bridge the gap from educational competency to clinical proficiency, and describe its use in the assessment of clinical proficiency of the athletic training student Background: A consistent challenge in curricular development for any athletic training education program (ATEP) is transforming formal classroom and psychomotor skill learning to the appropriate clinical proficiencies required by the standards for accreditation. Thus, we developed a method to address this challenge that incorporates the use of digital video technology. Description: We describe the use of video in the form of a digital video disc (DVD) as the means to evaluate and assess the student's achievement of specific clinical proficiencies. Additionally we give specific examples of the aspects of video analysis that we have addressed in actual encounters. We present this method as a means to perpetuate the concept of “learning over time.” Clinical Advantage(s): The use of video to analyze student performance during a clinical injury evaluation provides the means of (1) evaluating an athletic training student's clinical proficiency, (2) allowing student input into their psychomotor performance, and (3) developing archival data of student performance for re-evaluation and documentation of learning overtime. Conclusion(s): The use of video analysis represents an effective pedagogical method to educate athletic training students.