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This study aims to consider assurance of learning among undergraduate business students enrolled in capstone business strategy courses using the GLO-BUS competitive simulation. Gender, academic major and business core course performance were examined.

Participants were 595 undergraduate capstone business students from 21 course sections taught over a four-year period. Variables included learning assurance measures, simulation performance, gender, major, business core course grades, capstone course grade and cumulative grade point average. Correlations, linear regression, multiple regression and multivariate analysis of variance (MANOVA) were used to analyze the data.

Learning assurance report scores were strongly related to simulation performance. Simulation performance was related to capstone course grade, which, in turn, was significantly related to the grade point average (GPA). Core business courses were related to learning assurance and performance indicators. Significant differences for gender and degree major were found for academic performance measures. Women and men did not differ in simulation performance.

Limitations include the use of one simulation (GLO-BUS) and studying students at one university taught by one professor. Assurance of learning measures needs further study as factors in business program evaluation. Future research should analyze post-graduate performance and career achievements in relation to assurance of learning outcomes.

This study conducts empirical analyses of simulation learning that focuses entirely on direct measures, including student characteristics (gender, major), learning assurance measures, business core course grades, capstone course grades and student GPAs.

Many universities now offer courses online using learning management systems (LMS). Numerous studies have been conducted to assess the effectiveness of the LMS but few studies have examined how student online behavior within the course, or what they think about the online course, are related to their actual learning outcomes. The paper aims to discuss this issue.

In this study, student activity in an online business course was captured though learning analytics and assignments to determine if online activity and reflective learning impact final grade. A post-positivist ideology was employed. The dependent variable was the grade resulting from five assignments assessed using rubrics. Correlation, t-tests, multiple regression, surface response regression, General Linear Model (GLM)/F-tests, text analytics, analysis of means (ANOM), and cluster analysis were used to test the hypotheses.

Four statistically significant predictors of online student learning performance were identified: course logins, lesson reading, lesson quiz activity, and lesson quiz scores. This four factor model captured 78 percent of variance on course grade which is a strong effect and larger than comparative studies using learning analytics with online courses. Text analytics and ANOM conducted on student essays identified 17 reflective learning keywords that were grouped into five clusters to explain online student behavior.

First, from a pedagogy standpoint, encouraging students to complete more online lessons including quizzes, generally promotes learning, resulting in higher grades, which is a win:win for students and for the university. Second, from an IT perspective, the student pre and post testing resulted in statistically significant increase of IT-course knowledge, which puts students on a solid foundation to begin an online business course. Additionally, the link between students voicing IT problems but nonetheless scoring very well on the course certainly implies the development of IT self-efficacy, developed partly through the pre and post testing process. A clear link was established between course learning objectives and student learning performance by using a unique text analytics procedure.

The mixed-methods research design started with hypothesis testing using parametric and nonparametric techniques. Once a statistically significant predictive GLM was developed, qualitative data were collected from what the students thought as expressed in their last essay assignment. Text analytics was used to identify and statistically weight the 17 most frequent reflective learning keywords from student essays. A visual word cloud was presented. Parametric statistics were then used to partition the reflective learning keywords into grade boundaries. Nonparametric cluster analysis was used to group similar reflective keyword-grade associations together to form five clusters. The five clusters helped to explain student online behavior.

This chapter reports the results of a study of student performance in upper-level accounting courses, especially intermediate accounting I and cost accounting. Of particular interest is the performance of students who transferred the introductory accounting courses from a two-year institution versus native four-year students. We found that after controlling for a number of aptitudinal and demographic variables, transfer students performed at a significantly lower level than native students. On average, the difference was about 0.8 of a grade point. This study also provides evidence of grade inflation at two-year institutions relative to our four-year institution; documents a mean lag time of more than two years for community college students between taking principles of accounting courses and the upper-level courses; and shows that although the transfer shock lessens as the students continue in the major, it does not disappear. We also discuss the implications of our findings.

This paper focuses on the factors related to faculty workload in the context of resource scarcity to examine whether there is a relationship between them and grade inflation.

As for methodological novelty, the authors created an indicator of students' expectations about grades that is related to grade inflation and conducted regression analysis using cluster-robust error correction based on this indicator.

The results suggested that proper workload allocation among the faculty can mitigate grade inflation. Namely, such measures as control for concurrent courses, the length of courses and the labor intensity of the faculty are suggested for grade inflation prevention.

Academic literature posits that a steep increase in average grades might cause a long-term depreciation of the quality of higher education. This article is, therefore, focused on various factors connected with grade inflation in higher education. The authors highlighted problems associated with teaching evaluation imperfections, academic norm transformation and workload intensity.

As more students take online courses as part of their college curricula, the integrity of testing in an online environment becomes increasingly important. The potential for cheating on exams is generally considered to be higher in an online environment. One approach to compensate for the absence of a physical proctor is to use a remote proctoring service that electronically monitors the student during the examination period.

We examined the exam grades for 261 students taking two different upper division accounting courses to determine if a computer-based remote proctoring service reduced the likelihood of cheating, measured through lower exam scores, as compared to classroom proctoring and no proctoring. We examined both online and on-campus courses.

In qualitative and quantitative accounting courses, evidence shows that grades were significantly lower for students who were proctored using a remote proctoring service compared to students who were not proctored. In the quantitative course, remote proctoring resulted in significantly lower final exam scores than either classroom or no proctoring. However, in the qualitative course, both remote proctoring online and live proctoring in a classroom resulted in significantly lower final exam scores than no proctoring, and they are not statistically different from each other.

Academics and administrators should find these results helpful. The results suggest that the use of proctoring services in online courses has the potential to enhance the integrity of online courses by reducing the opportunities for academic dishonesty during exams.

This study sheds light on the prediction of success using cutoff scores for student grades adopted for a required Physics pathway course for study in a health professions program at King Saud University in Saudi Arabia. Data on course grade and GPA for approximately 10,000 students enrolled in this course between 2008–2014, were analyzed. Receiver Operating Characteristic (ROC) curve analysis was used to determine cutoffs for course grades using ranges of GPA. This procedure has promise as a new method for quantitatively arriving at cutoff scores using an external criterion requiring less human judgment than most existing standard setting methods. The cutoff scores produced show that GPAs of students who complete the Physics course yield successive performance tiers that are lower than expected. In addition, the correlation between GPA and course grade for Physics is only 0.63 and therefore only 39% of the variation in GPA explains course grade. As a result of the findings of the study, the decision was made to maintain the existing standards thereby requiring higher grades in the Physics course for students seeking to enter a health professions course of study.

ﻧﺗﻟا ﺎﮭﺗردﻗو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻠﻋ ءوﺿﻟا ﺔﯾﻟﺎﺣﻟا ﺔﺳاردﻟا طﻠﺳﺗ ﻲﻓ ﺔﺑﻠطﻟا حﺎﺟﻧ ﻰﻠﻋ ﺔﯾؤﺑﻲﻟوﻻا ءﺎﯾزﯾﻔﻟا ررﻘﻣ زﯾﻓ)145( ، دﻌﯾ يذﻟاوﻠﻋ ﺎﯾﺳﺎﺳا ﺎﺑﻠطﺗﻣكﻠﻣﻟا ﺔﻌﻣﺎﺟ ﻲﻓ ﺔﯾﺣﺻﻟا تﺎﺻﺻﺧﺗﻟا ﺔﺑﻠط ﻰ ﺔﻘﻠﻌﺗﻣﻟا تﺎﻧﺎﯾﺑﻟا ﻊﻣﺟ مﺗ دﻘﻓ ﺔﯾﻠﻋو ،ﺔﯾدوﻌﺳﻟا ﺔﯾﺑرﻌﻟا ﺔﻛﻠﻣﻣﻟﺎﺑ دوﻌﺳ نﻣ برﺎﻘﯾ ﺎﻣﻟ ررﻘﻣﻟا اذھ تﺎﺟردﺑ10000 ماوﻋﻻا نﯾﺑ ررﻘﻣﻟا اذﮭﺑ اوﻘﺣﺗﻟا نﯾذﻠﻟا ﺔﺑﻠطﻟا نﻣ2008 - 2014 .ﺔﯾﻣﻛارﺗﻟا مﮭﺗﻻدﻌﻣو ،م ﺗﻟو مادﺧﺗﺳا مﺗ دﻘﻓ ،تﺎﻧﺎﯾﺑﻟا هذھ لﯾﻠﺣ تﺎﯾﻠﻣﻌﻟا لﯾﻐﺷﺗ ﺔﯾﺻﺎﺧ ﻰﻧﺣﻧﻣReceiver Operating Characteristic (ROC) تﺎﺟردﻟا دﯾدﺣﺗﻟ نﻣ دﺣﻟاو ﺔﯾدﺣﻟا تﺎﺟردﻟا ﻰﻟا لوﺻوﻠﻟ ﺔﺛﯾدﺣﻟا ﺔﯾﻣﻛﻟا قرطﻟا نﻣ ﺔﻘﯾرطﻟا هذھ دﻌﺗ ثﯾﺣ ،ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﻣ ﺔﻔﻠﺗﺧﻣ تﺎﻗﺎطﻧﻟ ﺔﯾدﺣﻟارﯾﺛﺄﺗﻟا .يرﺷﺑﻟا نﻣﺿ نﺎﻛ ررﻘﻣﻟا اذھ زﺎﺗﺟا نﻣﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نا ﻰﻟا ترﺎﺷا دﻗ ﺎﮭﯾﻠﻋ لوﺻﺣﻟا مﺗ ﻲﺗﻟا ﮫﯾدﺣﻟا تﺎﺟردﻟا نﺎﻓ ﺔﯾﻠﻋو تﻐﻠﺑ ﺔﺑﻠطﻟا تﺎﺟردو ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا نﯾﺑ ﺔﯾطﺎﺑﺗرﻻا ﺔﻗﻼﻌﻟا نا ﺎﻣﻛ ،ﻊﻗوﺗﻣﻟا نﻣ لﻗا تﺎﻗﺎطﻧ0.63 ﻲﻧﻌﯾ ﺎﻣﻣ ، نا 39% نﻣتﺎﻧﯾﺎﺑﺗﻟا ﺔﯾﻣھا نﯾﺑﺗﯾ ﺞﺋﺎﺗﻧ نﻣ ﺔﯾﻠﻋ لوﺻﺣﻟا مﺗ ﺎﻣﻟ ﺎﻘﻓوو .رﻘﻣﻟا كﻟذ ﻲﻓ مﮭﺗﺎﺟرد رﯾﺳﻔﺗ ﻲﻓ مﮭﺳﺗ نا نﻛﻣﯾ ﺔﺑﻠطﻠﻟ ﺔﯾﻣﻛارﺗﻟا تﻻدﻌﻣﻟا ﻲﻓﺔظﻓﺎﺣﻣﻟا ﻰﻠﻋ ررﻘﻣﻟا رﯾﯾﺎﻌﻣﺔﯾﻟﺎﺣﻟا ﻊﻣدﯾﻛﺄﺗ لوﺻﺣﺔﺑﻠطﻟا تﺎﺻﺻﺧﺗﻟﺎﺑ قﺎﺣﺗﻟﻼﻟ نﯾﺑﻏارﻟاﺔﯾﺣﺻﻟا تﺎﺟرد ﻰﻠﻋﺔﻌﻔﺗرﻣ .ءﺎﯾزﯾﻔﻟا ررﻘﻣ ﻲﻓ

Digital learning has become a global trend. Partly or fully automatic learning systems are integrated into education in schools and universities on a previously unseen scale. Learning systems have a lot of potential for re-education, life-long learning and for increasing access to educational resources. Learning systems create massive amounts of data about learning behaviour. Analysing that data for educational decision making has become an important track of research. The purpose of this paper is to analyse data from an intermediate-level computer science course, which was taught to 141 students in spring 2018 at University of Turku, Department of Future Technologies, Finland.

The available variables included number of submissions, submission times, variables of groupwork and final grades. Associations between these variables were looked at to reveal patterns in students’ learning behaviour.

It was found that time usage differs per different grades so that students with grade 4 out of 5 used most time. Also, it was found that studying at night is connected to weaker learning outcomes than studying during daytime. Several issues in relation to groupwork were revealed. For example, associations were found between prior skills, preference for individual vs groupwork, and course learning outcomes.

The research was limited by the domain of available variables, which is a common limitation in learning analytics research.

The practical implications include important ideas for future research and interventions in digital learning.

The importance of research on soft skills, social skills and collaboration is highlighted.

The paper points a number of important ideas for future research. One important observation is that some research questions in learning analytics need qualitative approaches, which need to be added to the toolbox of learning analytics research.

The purpose of this study is to identify which of factors are associated with student performance in advanced accounting and auditing courses.

Students enrolled in a highly diversified, commuter, public university located in one of the largest cities in the USA provided responses to 12 questions used as independent variables.

Of the three variables used as proxies for motivation, the grade the student would like to make in the course was found to be significantly associated with student performance, but intention to take the CPA exam or attend graduate school were not. Additionally, the grade in intermediate accounting II and grade point average (used as proxies for actual ability) were found to be strong predictors of student performance. Self‐perceived reading and listening abilities had moderate to strong associations with student performance, but self‐perceived writing and math abilities did not. Finally, holding non‐accounting‐related jobs, working high numbers of hours per week, and taking on higher course loads during the semester are factors which were, surprisingly, not significantly correlated with student performance.

No prior study that we are aware of has considered the associations between motivation, actual ability, self‐perceived ability, and distraction factors and student performance in advanced level undergraduate accounting courses.

Social cognitive career theory (“SCCT”) suggests that positive feedback can influence educational choices. Introductory courses often provide students with their first opportunity to obtain feedback in a given discipline. As a result, SCCT hypothesizes that introductory courses grades will impact a student's decision to major in a given discipline. The purpose of this paper is to explore this hypothesis in the accounting domain.

Longitudinal data were collected from four cohorts of students registered at a Canadian university. The main hypothesis is tested by estimating a logistic regression.

A significant positive relationship is found between a student's introductory financial accounting (“IFA”) course grade and their decision to major in accounting. This decision to major in the discipline is not found to be affected by various student (e.g. biological sex or age) or instructor (e.g. whether the instructor holds a CPA designation or not) characteristics.

This study supports seminal and enduring research that emphasizes the IFA course as a gateway into the accounting major. As a result, educators should consider these findings when designing their IFA courses and the related student supports embedded within the IFA course.

Prior literature offers conflicting results on the relationship between IFA grades and student's choice to major in accounting. This study relies upon a theoretical framework, SCCT, to settle the debate. This study further extends the prior literature by exploring the impact of various student and instructor characteristics on the relationship between IFA grades and student's choice to major in accounting.

The purpose of this paper is to use a heutagogical approach to determine whether students enrolled in blended courses achieve higher grades relative to those enrolled in completely online courses, in addition to identifying demographic predictors of academic success in college courses involving Web-based modes of instruction.

Mixed models regression evaluated predictors of grade in terms of age, gender, instruction mode, graduate vs undergraduate status and full-time vs part-time load across 2,174 students (M = 27.6, SD = 9.54 years) enrolled in Web-based courses for a single term at a mid-sized public university in the northeastern USA.

In accordance with expectations, a significant main effect indicated higher grades among students enrolled in blended relative to completely online courses. Other predictors of academic success in Web-based courses included older age, female gender, graduate student status and part-time academic load. An interaction between age and gender on grade indicated the difference in performance between men and women diminished among older compared to younger students. Another interaction between age and instruction mode on successful course completion indicated a higher probability of success in blended courses among older students relative to their younger counterparts.

This study is limited by its cross-sectional design of large scope, which is incapable of addressing differences in online instructional styles and student motivation factors.

The current study offers newfound evidence that students enrolled in Web-based college courses may benefit from a blended instructional format, a finding that may be particularly evident among older students.