UTILIZATION AND EFFECT OF MULTIPLE CONTENT MODALITIES IN ONLINE HIGHER EDUCATION: SHIFTING TRAJECTORIES TOWARD SUCCESS THROUGH UNIVERSAL DESIGN FOR LEARNING

The idea that offering multiple means of representing course content will assist students of all abilities constitutes one pillar of Universal Design for Learning (UDL), a framework intended to address needs of students with disabilities while also holding relevance for all students. The efficacy of this UDL guideline lacks a verified empirical basis and therefore merits rigorous examination. My dissertation investigates the effect on learning outcomes of students using multiple modalities while learning course content (e.g., text, video, audio, interactive, or mixed content), targeting improving educational success for non-traditional online students. I investigate this effect for older undergraduates from a women’s institution who are predominantly low income and working mothers returning to school, many of whom are racial/ethnic minorities. Notably, challenges resulting from a lack of disability diagnosis and accommodation may be prevalent but hidden among these students. Traditional higher education typically does not serve such students well. Use of multiple modalities in class activities holds potential for improving their outcomes. Results show positive effects of using multiple modalities for learning content in courses across the curriculum presented in an adaptive learning system. Using a within-subjects study design, I found a medium-large positive effect size for knowledge gained across adaptive activities. Using an instrumental variables approach, I found a very large positive effect size for weekly assignment and quiz grades, and results suggest a large positive effect on course grade as well. I illustrate how combining knowledge of this effect with other information from the adaptive learning system and online tutoring in a Bayesian network analysis can predict where students may benefit from tutoring. This can inform potential support recommendations that would be particularly relevant when implementation of UDL-based design does not yet fully address students’ learning needs. These results provide the first evidence confirming an effect of UDL’s multiple modalities guideline on collegiate learning outcomes and illustrate how this information could be used to provide recommendations to students using a learning analytics perspective. Results have implications for researchers, faculty, course developers, instructional designers, analytics professionals, and institutions aiming to improve learning outcomes through a design-based approach

Who are Rural Students? How Definitions of Rurality Affect Research on College Completion

Given a revived national discourse about rural populations, more educational research on rural students is necessary, including ways that rural students transition to college and the success (or lack thereof) that they experience once there. However, the National Center for Education Statistics (NCES) has changed the definition of rurality used in each iterative dataset over the last few decades, casting doubt on the consistency of what is meant by the term rural. The purpose of this study is to: (a) communicate to the educational research audience various ways of defining rural students, and specifically how NCES has changed their definition of rurality over their last three major data collections; (b) demonstrate how conclusions about rural students’ and their college degree completion may differ based on these alternate NCES definitions; and (c) discuss how this specific example using NCES data relates to the wider landscape of research on rural students. Results show that conclusions about college degree completion change depending on the definition of rurality used for analysis. Therefore, the education research community should consider the options for defining rural students, report transparently about the choices made, consider the sensitivity of results to the definition of rurality, and ultimately build a more robust body of literature concerning rural students’ college success. Gaining definitional clarity will be beneficial, particularly for those who wish to translate their research into practical action for the benefit of rural students

STEM degree completion and first-generation college students. A cumulative disadvantage approach to the outcomes gap

STEM majors offer pathways to lucrative careers but are often inac-cessible to first-generation students. Using data from the Education Longitudinal Study, we conducted descriptive statistics, regression analyses, and group comparisons to examine differences between first-generation students and continuing-generation students across STEM degree, non-STEM degree, dropout, and no degree completion. Findings illuminate that generation status is related to STEM completion, but other factors are driving this association; for example, pre-college STEM factors have significant predictive power. Our implications suggest a need to further examine pre-college and transfer pathways to STEM and to explore the limitations of first-generation status as a categorization

Narrowed Gaps and Persistent Challenges: Examining Rural-Nonrural Disparities in Postsecondary Outcomes over Time

Empirical studies have concluded that rural students experience lower rates of college enrollment and degree completion compared to their nonrural peers, but this literature needs to be expanded and updated for a continually changing context. This article examines the rural-nonrural disparities in students’ postsecondary trajectories, influences, and outcomes. By comparing results to past research using similar national data and an identical design, we are able to examine change over time. Results show narrowed gaps from the 1990s into the 2000s, but with rural students still facing persistent challenges and experiencing lower average rates of college enrollment and degree completion

The Influence of STEM Definitions for Research on Women\u27s College Attainment

Background Prior research has inconsistently operationalized Science, Technology, Engineering, and Math (STEM) fields, presenting an interpretation challenge. A content analysis of 51 quantitative, gender-focused, higher education-oriented, STEM-related studies in the ERIC database published between January 2010 and July 2018 revealed that only 13 articles used an existing STEM definition. In 15, STEM was not explicitly defined, and others defined STEM independently. This wide range of definitions may lead to confusion or misrepresentation of findings for interventions and practices to support women in STEM. To illustrate the issue and prompt recommendations for future research, this study uses data from the United States National Center for Education Statistics’ Education Longitudinal Study (ELS:2002/12) to investigate the connection between STEM definition and the outcome of college degree completion, comparing results by gender for five ways of operationalizing STEM fields. Results We found the size, direction, and significance of the gender gap depended on STEM operationalization. When STEM was defined as high paradigm fields, the odds of women attaining a non-STEM degree were higher than otherwise. When social science fields were included in STEM, there was no statistically significant difference by gender. When looking specifically at fields considered related to science and engineering, the direction of the relationship was reversed. Conclusion While our findings follow expectations about social science fields and gender, it is noteworthy that results regarding STEM degree completion by gender for science and engineering-related fields were opposite those of high paradigm STEM fields. This result highlights that the definition of STEM matters, and inconsistent operationalization in the literature presents an interpretation challenge. We argue the field should strive to find common categorizations of STEM that retain the legitimate variation in how STEM can and should be defined, while providing a basis for consistent comparison. We recommend researchers and practitioners developing research-based practices: 1) interpret research findings understanding potential inconsistency from different STEM operationalizations, 2) explicitly describe STEM operational definitions to enable comparing findings, 3) routinely analyze sensitivity to alternate STEM definitions, and 4) find common STEM categorizations that retain legitimate variation while providing a basis for consistent comparison

Financial Planning for College: Parental Preparation and Capital Conversion

This study explores the conversion of cultural capital into economic capital, and specifically financial capital in the form of parental financial planning for children’s college education, including reported financial preparations and savings. Using data from the Education Longitudinal Study (ELS:2002), logistic regression-based analyses of aspects of cultural capital indicated that parental involvement exhibited the most prevalent relationship with financial planning and the amount saved, and that parents’ expectations, but not their aspirations, corresponded to engagement in financial planning. Findings support the conclusion that some parents convert part of their cultural capital to financial capital in preparation for paying for their child’s college education, perhaps representing a typically hidden facet of social class reproduction

Socioeconomic Disparities in the Use of College Admission-Enhancing Strategies among High School Seniors from the 1990s to 2000s

This study examines whether strategies commonly used by high school students for enhancing their chances of gaining college admission may contribute to social inequality in postsecondary education. Comparisons are made between nationally representative samples of high school seniors across two decades, from the early 1990s to the early 2000s. The analyses identify the extent to which students’ SES was associated with the use of admission-enhancing strategies, determine the extent to which the relationships changed across a two-decade period, and examine the role of academic achievement in this process. Results confirm that higher SES students are more likely to employ admission-enhancing strategies than lower SES students, but more importantly that this gap widened over time. These findings suggest that admission-enhancing strategies may be partially responsible for maintaining socioeconomic disparities through education

College Enhancement Strategies and Socioeconomic Inequality

The study provides new information on the relationships between students’ socioeconomic backgrounds, utilization of college enhancement strategies, and subsequent 4-year college enrollment. Enhancement strategies represent student behaviors used to bolster the competitiveness of a college application, such as Advanced Placement exams and a variety of extracurricular activities. By drawing on two national datasets that span the 1990s (NELS) and the 2000s (ELS), the study uncovers how these relationships have changed during a period marked by escalating demand for college and growing class inequality. The findings provide partial evidence of class adaptation (Alon in Am Soc Rev 74:731–755, 2009) based on the combination of increased use of multiple enhancement strategies (“high overall use”) among higher SES students and increased influence of high overall enhancement strategy use in predicting college enrollment, particularly selective college enrollment. Implications are discussed in terms of the higher education system and pervasive social inequality

Towards more replicable content analysis for learning analytics

Content analysis (CA) is a method frequently used in the learning sciences and so increasingly applied in learning analytics (LA). Despite this ubiquity, CA is a subtle method, with many complexities and decision points affecting the outcomes it generates. Although appearing to be a neutral quantitative approach, coding CA constructs requires an attention to decision making and context that aligns it with a more subjective, qualitative interpretation of data. Despite these challenges, we increasingly see the labels in CA-derived datasets used as training sets for machine learning (ML) methods in LA. However, the scarcity of widely shareable datasets means research groups usually work independently to generate la- belled data, with few attempts made to compare practice and results across groups. A risk is emerging that different groups are coding constructs in different ways, leading to results that will not prove replicable. We report on two replication studies using a previously reported construct. A failure to achieve high inter-rater reliability suggests that coding of this scheme is not currently replicable across different research groups. We point to potential dangers in this result for those who would use ML to automate the detection of various educationally relevant constructs in LA

Assessing Working Memory in Mild Cognitive Impairment with Serial Order Recall.

BACKGROUND: Working memory (WM) is often assessed with serial order tests such as repeating digits backward. In prior dementia research using the Backward Digit Span Test (BDT), only aggregate test performance was examined. OBJECTIVE: The current research tallied primacy/recency effects, out-of-sequence transposition errors, perseverations, and omissions to assess WM deficits in patients with mild cognitive impairment (MCI). METHODS: Memory clinic patients (n = 66) were classified into three groups: single domain amnestic MCI (aMCI), combined mixed domain/dysexecutive MCI (mixed/dys MCI), and non-MCI where patients did not meet criteria for MCI. Serial order/WM ability was assessed by asking participants to repeat 7 trials of five digits backwards. Serial order position accuracy, transposition errors, perseverations, and omission errors were tallied. RESULTS: A 3 (group)×5 (serial position) repeated measures ANOVA yielded a significant group×trial interaction. Follow-up analyses found attenuation of the recency effect for mixed/dys MCI patients. Mixed/dys MCI patients scored lower than non-MCI patients for serial position 3 (p \u3c 0.003) serial position 4 (p \u3c 0.002); and lower than both group for serial position 5 (recency; p \u3c 0.002). Mixed/dys MCI patients also produced more transposition errors than both groups (p \u3c 0.010); and more omissions (p \u3c 0.020), and perseverations errors (p \u3c 0.018) than non-MCI patients. CONCLUSIONS: The attenuation of a recency effect using serial order parameters obtained from the BDT may provide a useful operational definition as well as additional diagnostic information regarding working memory deficits in MCI