scholarly journals An Examination of Student Success within Canadian Higher Education: Fifty Years of Findings and Recommendations for the Future

2021 ◽  
pp. 13-32
Author(s):  
Jason R. Holmes
Keyword(s):  
Higher Education ◽  
Academic Success ◽  
Student Success ◽  
Large Data ◽  
Future Research ◽  
Data Sets ◽  
College Performance ◽  
Arts And Humanities ◽  
Canadian Higher Education ◽  
Wide Range

This article explores the student success literature published within the Canadian Journal of Higher Education (CJHE) over the last fifty years. Sixty articles were thematically organized into seven component measures of student success to present consistent themes that have persisted within the CJHE from inception in 1971 to 2020. Analysis demonstrates that there has been a disproportionate interest in some aspects of student success such as post-college performance, while other areas such as educational attainment and student engagement have lagged considerably behind in focus. Scholars have presentedongoing concerns supported by a wide range of data regarding the underemployment of graduates from Arts and Humanities, the sparse professorial landscape and the underutilization of Canadian PhD graduates in the workforce, debate on student competence and skill measurement, and the lack of large data sets on student persistence. Results suggest that a continuous effort is required to understand and support student success in a variety of formats—both within the academy and out in the workforce. Thus, this article concludes with a discussion and recommendations for future research avenues in the field of academic success and various subfields that may be of interest to higher education scholars and those who support student success.

Electronic Records Management - An Old Solution to a New Problem

Big Data ◽  
2016 ◽  
pp. 2249-2274
Author(s):  
Chinh Nguyen ◽  
Rosemary Stockdale ◽  
Helana Scheepers ◽  
Jason Sargent
Keyword(s):  
Big Data ◽  
Rapid Development ◽  
Large Data ◽  
Large Data Sets ◽  
Electronic Records ◽  
Future Research ◽  
Records Management ◽  
Data Sets ◽  
Interactive Nature ◽  
Electronic Records Management

The rapid development of technology and interactive nature of Government 2.0 (Gov 2.0) is generating large data sets for Government, resulting in a struggle to control, manage, and extract the right information. Therefore, research into these large data sets (termed Big Data) has become necessary. Governments are now spending significant finances on storing and processing vast amounts of information because of the huge proliferation and complexity of Big Data and a lack of effective records management. On the other hand, there is a method called Electronic Records Management (ERM), for controlling and governing the important data of an organisation. This paper investigates the challenges identified from reviewing the literature for Gov 2.0, Big Data, and ERM in order to develop a better understanding of the application of ERM to Big Data to extract useable information in the context of Gov 2.0. The paper suggests that a key building block in providing useable information to stakeholders could potentially be ERM with its well established governance policies. A framework is constructed to illustrate how ERM can play a role in the context of Gov 2.0. Future research is necessary to address the specific constraints and expectations placed on governments in terms of data retention and use.

scholarly journals Graph representation learning: a survey

2020 ◽  
Vol 9 ◽  
Author(s):  
Fenxiao Chen ◽  
Yun-Cheng Wang ◽  
Bin Wang ◽  
C.-C. Jay Kuo
Keyword(s):  
Graph Embedding ◽  
Large Data ◽  
Representation Learning ◽  
Graph Representation ◽  
Data Sets ◽  
Graph Data ◽  
Graph Properties ◽  
Wide Range ◽  
Regular Lattices ◽  
Low Dimensional

Abstract Research on graph representation learning has received great attention in recent years since most data in real-world applications come in the form of graphs. High-dimensional graph data are often in irregular forms. They are more difficult to analyze than image/video/audio data defined on regular lattices. Various graph embedding techniques have been developed to convert the raw graph data into a low-dimensional vector representation while preserving the intrinsic graph properties. In this review, we first explain the graph embedding task and its challenges. Next, we review a wide range of graph embedding techniques with insights. Then, we evaluate several stat-of-the-art methods against small and large data sets and compare their performance. Finally, potential applications and future directions are presented.

scholarly journals Determining Academic Success in Students with Disabilities in Higher Education

2019 ◽  
Vol 8 (2) ◽  
pp. 16 ◽  
Author(s):  
Stephanie Bain De Los Santos ◽  
Lori Kupczynski ◽  
Marie-Anne Mundy
Keyword(s):  
Higher Education ◽  
Academic Success ◽  
Student Success ◽  
Students With Disabilities ◽  
Faculty Involvement ◽  
University Administrators ◽  
College And University ◽  
High School To College ◽  
Transition From High School ◽  
Institutional Support Services

Students with disabilities have not been fully welcomed in higher education in spite of litigation, court cases, and positive shifts in public perceptions. The transition from high school to college is challenging for students without disabilities. Students with disabilities often get overlooked by their institution and overwhelmed during this transition, contributing to an achievement gap for these students. Student success is measured by retention, academic achievement, and on-time graduation. This research study examined how student success was impacted by a student’s registration with the campus disability office, use of accommodations, and use of institutional and social support systems. This study explored a new frontier of research that dispels the myth that students with disabilities are a homogenous group. The results of this study can be used to increase knowledge regarding students with disabilities and their success in higher education. The results will assist college and university administrators as well as staff in disability services offices in tracking the success of accommodations for students with disabilities. This study can help university administration to better understand the benefits of institutional support services as well as encourage faculty involvement in implementing accommodations and helping students see the benefit of student registration with the campus office of disabilities.

The Role of Higher Education and Peer Mentoring in Student Success

2020 ◽  
pp. 50-56
Author(s):  
Y. Deneice Berry
Keyword(s):  
Higher Education ◽  
Academic Success ◽  
Student Success ◽  
Vulnerable Populations ◽  
Peer Mentoring ◽  
Degree Attainment ◽  
Mentoring Program ◽  
College Administrators ◽  
Barriers And Challenges

Students are faced with many challenges before entering college. Those challenges make it difficult for students to reach degree attainment. Vulnerable populations are predisposed to barriers and challenges that impede their progress to achieving academic success. By integrating peer mentoring as a framework, we will better understand how to serve our vulnerable populations and the role higher education institutions play to meet students where they are. College administrators are typically responsible for strengthening the values, mission, and goals of the college. However, do they have a social responsibility to also make sure all students succeed? This chapter provides a student success tool that addresses some of those barriers while promoting student success. This chapter will provide the need for a mentoring program for college students and will discuss various peer mentoring models that can assist with retention and degree attainment.

Assessment in American Higher Education: The Role of Admissions Tests

2019 ◽  
Vol 683 (1) ◽  
pp. 130-148 ◽  
Author(s):  
Rebecca Zwick
Keyword(s):  
Higher Education ◽  
United States ◽  
The United States ◽  
College Performance ◽  
Admissions Tests ◽  
Higher Education System ◽  
Wide Range ◽  
Test Optional ◽  
The Impact

In this article, I review the role of college admissions tests in the United States and consider the fairness issues surrounding their use. The two main tests are the SAT, first administered in 1926, and the ACT, first given in 1959. Scores on these tests have been shown to contribute to the prediction of college performance, but their role in the admissions process varies widely across colleges. Although test scores are consistently listed as one of the most important admissions factors in national surveys of postsecondary institutions, an increasing number of schools have adopted “test-optional” policies. At these institutions, test score requirements are seen as a barrier to campus diversity because of the large performance gaps among ethnic and socioeconomic groups. Fortunately, the decentralized higher education system in the United States can accommodate a wide range of admissions policies. It is essential, however, that the impact of admissions policy changes be studied and that the resource implications of these changes be thoroughly considered.

scholarly journals Toward Psychoinformatics: Computer Science Meets Psychology

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Christian Montag ◽  
Éilish Duke ◽  
Alexander Markowetz
Keyword(s):  
Computer Science ◽  
Online Social Network ◽  
Large Data ◽  
Research Field ◽  
Large Data Sets ◽  
Future Research ◽  
Data Sets ◽  
Psychological Traits ◽  
Scientific Methods ◽  
Insight Into

The present paper provides insight into an emerging research discipline calledPsychoinformatics. In the context ofPsychoinformatics, we emphasize the cooperation between the disciplines of psychology and computer science in handling large data sets derived from heavily used devices, such as smartphones or online social network sites, in order to shed light on a large number of psychological traits, including personality and mood. New challenges await psychologists in light of the resulting “Big Data” sets, because classic psychological methods will only in part be able to analyze this data derived from ubiquitous mobile devices, as well as other everyday technologies. As a consequence, psychologists must enrich their scientific methods through the inclusion of methods from informatics. The paper provides a brief review of one area of this research field, dealing mainly with social networks and smartphones. Moreover, we highlight how data derived fromPsychoinformaticscan be combined in a meaningful way with data from human neuroscience. We close the paper with some observations of areas for future research and problems that require consideration within this new discipline.

scholarly journals Academic Success: a student’s guide to studying at university

2019 ◽  
Author(s):  
Karen Hudson
Keyword(s):  
Higher Education ◽  
Academic Success ◽  
Prior Knowledge ◽  
Communicative Practices ◽  
Academic Knowledge ◽  
Disciplinary Discourse ◽  
Limited Experience ◽  
Wide Range ◽  
English Speaking

Aimed at students with limited experience of the culture and conventions of English-speaking universities, this book introduces readers to a wide range of academic communicative practices. It assumes no prior knowledge or experience of the (mostly) unwritten behaviours, attitudes and values required for academic success and provides a comprehensive breakdown of these, clarified throughout with examples, explanations and practical guidance.The book’s scope is broad, rather than deep, and therefore represents a useful and pragmatic introductory text for any student preparing for a transition or return to higher education. The text is underpinned throughout by two recurring themes that are directly transferable into LD practice. The idea that academic knowledge is developed and communicated via debate and argument is directly linked to the notion of ‘academic apprenticeship’ in which students are encouraged to begin participation in active and current disciplinary discourse.  

Social Stratification in Higher Education

2009 ◽  
Vol 111 (10) ◽  
pp. 2347-2384 ◽  
Author(s):  
Eric Grodsky ◽  
Erika Jackson
Keyword(s):  
Higher Education ◽  
Social Stratification ◽  
Research Question ◽  
Behavioral Model ◽  
Future Research ◽  
Data Sets ◽  
Behavioral Theories ◽  
Past Half Century ◽  
The Relationship ◽  
Background Context

Background/Context Over the past half century, scholars in a variety of fields have contributed to our understanding of the relationship between higher education and social stratification. We review this literature, highlighting complementarities and inconsistencies. Purpose/Objective/Research Question/Focus of Study We situate our review of the literature on inequality and higher education in the context of a behavioral model of postsecondary participation that takes into account the actions of both students and institutions. Conclusions/Recommendations We recommend that researchers continue to engage in cross-disciplinary dialogues around challenges in postsecondary research and policy, advocate for an increase in the use of experimental designs, and encourage the development of linkages across administrative data sets. We also recommend that future research improve the alignment among behavioral theories, proposed interventions, study design, and analytic techniques.

scholarly journals Toward an Anti-Imperialistic Critical Race Analysis of the Model Minority Myth

2020 ◽  
Vol 90 (4) ◽  
pp. 542-579
Author(s):  
Varaxy Yi ◽  
Jacqueline Mac ◽  
Vanessa S. Na ◽  
Rikka J. Venturanza ◽  
Samuel D. Museus ◽  
...  
Keyword(s):  
Higher Education ◽  
Academic Success ◽  
Model Minority ◽  
Future Research ◽  
Deficit Thinking ◽  
Current Analysis ◽  
Model Minority Myth ◽  
The Past ◽  
Literature Reviews ◽  
Race Analysis

Over the past three decades, many higher education scholars have engaged in efforts to counter the stereotype that Asian Americans achieve universal and unparalleled academic success. While most of these scholars adopt an anti-oppression approach, some researchers have claimed that this literature reinforces oppressive deficit paradigms. To understand this conflict in existing literature, the current authors utilize an anti-imperialistic approach to analyze scholarship on the model minority myth. The current analysis reveals little evidence that research on the myth reinforced hegemonic deficit thinking. Instead, authors find that scholars largely utilized complex and multifaceted antideficit approaches, challenged dominant essentialist model minority frames, engaged in strategic (anti-)essentialism to navigate complex pan-racial contexts, and reframed the myth to achieve diverse purposes that speak to different audiences. Several implications for conducting critiques of literature reviews and future research on the myth are discussed.

scholarly journals 0062 Improved Circadian Data Ordering in the Presence of Biological and Technical Confounds

SLEEP ◽  
2020 ◽  
Vol 43 (Supplement_1) ◽  
pp. A24-A26
Author(s):  
J Hammarlund ◽  
R Anafi
Keyword(s):  
Machine Learning ◽  
Network Architecture ◽  
Large Data ◽  
Data Sets ◽  
Sample Collection ◽  
Circadian Phase ◽  
Confounding Variables ◽  
Wide Range ◽  
Fully Connected ◽  
Genome Scale

Abstract Introduction We recently used unsupervised machine learning to order genome scale data along a circadian cycle. CYCLOPS (Anafi et al PNAS 2017) encodes high dimensional genomic data onto an ellipse and offers the potential to identify circadian patterns in large data-sets. This approach requires many samples from a wide range of circadian phases. Individual data-sets often lack sufficient samples. Composite expression repositories vastly increase the available data. However, these agglomerated datasets also introduce technical (e.g. processing site) and biological (e.g. age or disease) confounders that may hamper circadian ordering. Methods Using the FLUX machine learning library we expanded the CYCLOPS network. We incorporated additional encoding and decoding layers that model the influence of labeled confounding variables. These layers feed into a fully connected autoencoder with a circular bottleneck, encoding the estimated phase of each sample. The expanded network simultaneously estimates the influence of confounding variables along with circadian phase. We compared the performance of the original and expanded networks using both real and simulated expression data. In a first test, we used time-labeled data from a single-center describing human cortical samples obtained at autopsy. To generate a second, idealized processing center, we introduced gene specific biases in expression along with a bias in sample collection time. In a second test, we combined human lung biopsy data from two medical centers. Results The performance of the original CYCLOPS network degraded with the introduction of increasing, non-circadian confounds. The expanded network was able to more accurately assess circadian phase over a wider range of confounding influences. Conclusion The addition of labeled confounding variables into the network architecture improves circadian data ordering. The use of the expanded network should facilitate the application of CYCLOPS to multi-center data and expand the data available for circadian analysis. Support This work was supported by the National Cancer Institute (1R01CA227485-01)

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