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Abstract Developmental education (dev-ed) aims to help students acquire knowledge and skills necessary to succeed in college-level coursework. The traditional prerequisite approach to postsecondary dev-ed—where students take remedial courses that do not count toward a credential—appears to stymie progress toward a degree. At community colleges across the country, most students require remediation in math, creating a barrier to college-level credits under the traditional approach. Corequisite coursework is a structural reform that places students directly into a college-level course in the same term they receive dev-ed support. Using administrative data from Texas community colleges and a regression discontinuity design, we examine whether corequisite math improves student success compared with traditional prerequisite dev-ed. We find that corequisite math quickly improves student completion of math requirements without any obvious drawbacks, but students in corequisite math were not substantially closer to degree completion than their peers in traditional dev-ed after 3 years.
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Math matters or maybe not: An astonishing independence between math and rate of learning in chemistry
Research spanning nearly a century has found that math plays an important role in the learning of chemistry. Here, we use a large dataset of student interactions with online courseware to investigate the details of this link between math and chemistry. The activities in the courseware are labeled against a list of knowledge components (KCs) covered by the content, and student interactions are tracked over a full semester of general chemistry at a range of institutions. Logistic regression is used to model student performance as a function of the number of opportunities a student has taken to engage with a particular KC. This regression analysis generates estimates of both the initial knowledge and the learning rate for each student and each KC. Consistent with results from other domains, the initial knowledge varies substantially across students, but the learning rate is nearly the same for all students. The role of math is investigated by labeling each KC with the level of math involved. The overwhelming result from regressions based on these labels is that only the initial knowledge varies strongly across students and across the level of math involved in a particular topic. The student learning rate is nearly independent of both the level of math involved in a KC and the prior mathematical preparation of an individual student. The observation that the primary challenge for students lies in initial knowledge, rather than learning rate, may have implications for course and curriculum design.
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- Award ID(s):
- 2016929
- PAR ID:
- 10558589
- Publisher / Repository:
- ChemRxiv
- Date Published:
- Format(s):
- Medium: X
- Institution:
- Carnegie Mellon University
- Sponsoring Org:
- National Science Foundation
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Wright, L Kate (Ed.)ABSTRACT Quantitative reasoning is a critical skill in biology and has been highlighted as a core competency byVision and Change. Despite its importance, students often struggle to apply mathematical skills in new contexts in biology, a process called transfer of knowledge. However, the supports and barriers that students perceive for this process remain unclear. To explore this further, we interviewed undergraduate students in an introductory biology lab course about how they understand and report the transfer of quantitative skills in these courses. We then applied these themes to the Step Back, Translate, and Extend (SBTE) framework to examine student perceptions of the supports and barriers to their knowledge transfer. Students reported different supports and barriers at each level of the transfer process. At the first step of the framework, the recognition level, students reported reflecting on previous chemistry, statistics, and physics learning as helpful cues to indicate a transfer opportunity. Others, however, reported perceiving math and science as separate subjects without overlap, causing a disconnect in their recognition of transferable knowledge. In the second level of the framework, students recall previous learning. Students reported repetition and positive dispositions toward science and math as supportive factors. In contrast, gaps of time between initial learning and new contexts and negative dispositions hindered recall ability. The final level of the SBTE framework focuses on application. Students reported being better able to apply previous learning to new contexts in the biology lab when they could relate their applied skills to “real-world” applications, external motivating factors, and future career goals. These students also reported proactively seeking outside resources to fill gaps in their understanding. Generating data in a lab setting was also mentioned by students as both a supportive factor of application when they felt confident in their answers and a hindrance to application when they felt unsure about its accuracy.more » « less
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null (Ed.)A well-established literature base identifies a portion of students enrolled in post-secondary General Chemistry as at-risk of failing the course based on incoming metrics. Learning about the experiences and factors that lead to this higher failure rate is essential toward improving retention in this course. This study examines the relationship between study habits and academic performance for at-risk students in General Chemistry. Students who were in the bottom quartile of SAT math scores were identified as at-risk students. The study habits of General Chemistry students, both those identified as at-risk and those not identified were measured by text message inquiries. The text message asked ‘‘Have you studied for General Chemistry I in the past 48 hours? If so, how did you study?” twice a week throughout a semester. Student responses to the messages were used to calculate the frequency of studying throughout the term. The results from a multiple regression analysis showed that high frequency of studying could mitigate the difference between at-risk and non-at-risk students on final exam scores. Additionally, the quality of studying for six at-risk students was analyzed by student interviews in concert with their text message responses. The results indicated that the quality of studying is not necessarily linked to frequency of studying and both quality and frequency can play a role in at-risk students' academic performance. The results presented offer a path for at-risk students to succeed in General Chemistry and the methodology presented offers a potential avenue for evaluating future efforts to improve student success.more » « less
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A longstanding goal of learner modeling and educational data min-ing is to improve the domain model of knowledge that is used to make inferences about learning and performance. In this report we present a tool for finding domain models that is built into an exist-ing modeling framework, logistic knowledge tracing (LKT). LKT allows the flexible specification of learner models in logistic re-gression by allowing the modeler to select whatever features of the data are relevant to prediction. Each of these features (such as the count of prior opportunities) is a function computed for a compo-nent of data (such as a student or knowledge component). In this context, we have developed the “autoKC” component, which clus-ters knowledge components and allows the modeler to compute features for the clustered components. For an autoKC, the input component (initial KC or item assignment) is clustered prior to computing the feature and the feature is a function of that cluster. Another recent new function for LKT, which allows us to specify interactions between the logistic regression predictor terms, is com-bined with autoKC for this report. Interactions allow us to move beyond just assuming the cluster information has additive effects to allow us to model situations where a second factor of the data mod-erates a first factor.more » « less
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Objective We live in an increasingly multicultural society which is reflected in the student population. In the community college (CC) setting, students from underrepresented groups are over-represented in remedial math courses and are less likely to complete the sequence. The extant literature suggests higher levels of acculturation, both cultural adoption and cultural maintenance, support academic success. Working memory (WM) is a well-known domain-general predictor of mathematical development and has been shown to relate to math achievement r = .38. Given this moderate relation, additional predictors of math achievement warrant investigation. In the present study, we investigated the potential moderational role of acculturation (cultural adoption and maintenance), on the WM-math relation in a diverse group of CC students (n = 94). Math was assessed both by a standardized measure of math computation and a measure of “everyday math” word problems including medical and financial management. We expected that higher levels of acculturation (adoption and maintenance) would decreasing WM load (via cognitive load) and aid math performance. At higher levels of acculturation, the WM-math relation was hypothesized approximate meta analytic findings, r = .38. Alternatively, at low levels of acculturation, the WM-math correlation was anticipated to be attenuated due to the added variability in culture and the negative impact low acculturation levels have on WM by increasing cognitive load. Participants and Methods A diverse sample of CC students (ages 18-25) who were enrolled in a math course were included. Participants completed an online survey covering demographic and cultural domains, then completed an in-person cognitive testing session to assess language abilities, WM, and math ability. Bivariate correlations and regression based moderation analyses were used. Post-hoc analyses were conducted to assess for three-way interactions with baseline verbal or math abilities. Results WM-math correlations averaged r = .38. Acculturation did not significantly relate to either outcome variable. Neither cultural adoption (computations: F=1.68, p =.199; word problems: F=.42, p =.521 ) nor cultural maintenance (computations: F=.83, p = .364; word problems: F=.36, p = .550) moderated the WM-math relations. Post-hoc analyses revealed significant three-way interactions between cultural adoption and math computation across different levels of vocabulary (F=4.66, p = .034) and math abilities (F= 6.16 p = .015). Conclusion The hypothesized moderational role of acculturation on the WM-math relation was not supported. Post-hoc analyses, however, revealed that the cultural adoption-math relationship varied across different levels of vocabulary and math abilities, although not in the direction anticipated. Finding suggest complex relationships between the WM, acculturation, and math such that acculturation does impact math performance when either vocabulary or math abilities are strong. At low levels of math or vocabulary, students’ WM may already be overtaxed, such that higher acculturation levels cannot benefit the student. Whereas when baseline abilities are average/high, increased cultural adoption can benefit the student by potentially decreasing cognitive load and freeing additional WM capacity which can be applied to the task. Findings could identify patterns of students at risk for math failure and inform future intervention/policy development to address their needs and support success.more » « less
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Accepted Manuscript1.0
- Posted Content:
- https://doi.org/10.26434/chemrxiv-2024-bms6x
