The Collegiate Learning Assessment: facts and fantasies.

Eval Rev

Council for Aid to Education, USA.

Published: October 2007

The Collegiate Learning Assessment (CLA) is a computer administered, open-ended (as opposed to multiple-choice) test of analytic reasoning, critical thinking, problem solving, and written communication skills. Because the CLA has been endorsed by several national higher education commissions, it has come under intense scrutiny by faculty members, college administrators, testing experts, legislators, and others. This article describes the CLA's measures and what they do and do not assess, how dependably they measure what they claim to measure, and how CLA scores differ from those on other direct and indirect measures of college student learning. For instance, analyses are conducted at the school rather than the student level and results are adjusted for input to assess whether the progress students are making at their school is better or worse than what would be expected given the progress of "similarly situated" students (in terms of incoming ability) at other colleges.

Download full-text PDF

Source
http://dx.doi.org/10.1177/0193841X07303318DOI Listing

Publication Analysis

Top Keywords

collegiate learning
8
learning assessment
8
assessment facts
4
facts fantasies
4
fantasies collegiate
4
assessment cla
4
cla computer
4
computer administered
4
administered open-ended
4
open-ended opposed
4

Similar Publications

Aviation College is a higher education institution that shifted to e-Learning as the education platform during the COVID-19 Pandemic. This shift has posed challenges, especially in developing countries like the Philippines. This study aims to evaluate students' intentions toward using an e-learning platform at a collegiate aviation institution during the pandemic by employing an integrated extended Technology Acceptance Model (TAM) and Seddon's Information System (IS) Success Model.

View Article and Find Full Text PDF

Physical activity (PA) is recommended in clinical practice guidelines as effective for the management of polycystic ovary syndrome (PCOS). However, adherence to PA interventions is low in this population, and long-term uptake of PA is a challenge. We conducted a feasibility trial of two PA interventions for women with PCOS.

View Article and Find Full Text PDF
Article Synopsis
  • * A study analyzed 174,878 student-athletes to assess the frequency of low scores on a concussion management test (ImPACT) for those with self-reported ADHD and/or LD, comparing them to a control group without these disorders.
  • * Results indicated that student-athletes with LD frequently scored low on the ImPACT (30-37%) and those with both ADHD and LD also showed significant low scoring rates (24-31%), highlighting the need for better understanding of these conditions in concussion assessments.
View Article and Find Full Text PDF

Exploring the breadth of medicine: 8-year outcomes of a brief clinical summer immersion for premedical students.

BMC Med Educ

November 2024

Department of Medicine, Division of Primary Care and Population Health, Stanford University School of Medicine, Stanford Clinical Summer Internship, Stanford, CA, USA.

Article Synopsis
  • The Stanford Clinical Summer Internship (CSI) was evaluated to assess its effectiveness in exposing high school and college students to various healthcare careers, emphasizing engagement in both in-person and virtual formats.
  • Survey results from 173 participants revealed that a significant majority felt the program broadened their medical perspectives, increased their interest in healthcare careers, and provided valuable clinical skills, with minimal differences noted between high school and college students.
  • In-person participants valued friendships formed during the program more, while virtual participants showed a stronger interest in research careers; overall, the internship positively influenced the educational and career paths of many respondents.
View Article and Find Full Text PDF

Screening ionic liquids (ILs) with low viscosity, low toxicity, and high CO absorption using machine learning (ML) models is crucial for mitigating global warming. However, when candidate ILs fall into the extrapolation zone of ML models, predictions may become unreliable, leading to poor decision-making. In this study, we introduce a "representation uncertainty" (RU) approach to quantify prediction uncertainty by employing four IL representations: molecular fingerprint, molecular descriptor, molecular image, and molecular graph.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!