Quantitative Reasoning Report
Fall 2024 and Spring 2025
Overview
Virginia Tech has chosen to measure two outcomes within the Quantitative and Computational Thinking area of the Pathways general education program for the assessment of quantitative reasoning. These two outcomes were chosen based on their alignment with the concept of Quantitative Reasoning.
Quantitative thinking is the formulation of questions that can be addressed using mathematical principles, leading to answers that include reliable and usable measures of accuracy. Computational thinking is the ability to conceive meaningful, information-based representations of the world that can be effectively manipulated using a computer. (Students take three courses in this area of the curriculum.)
During the Fall 2024 and Spring 2025 semesters, Virginia Tech sampled 89 course sections that addressed the Core Concept of Quantitative and Computational Thinking (QCT). In addition, some sections sampled for other Pathways Core Concepts also covered QCT. Instructors of sampled sections were asked to submit data for all Core Concepts. The final group of sections included in the analyses below were sections that were not required to submit data but contributed data voluntarily. As a result, 108 sections reported data for QCT.
Table 1 summarizes the number of Pathways sections sampled, the number reporting data, and the enrollment totals included in the analyses for QCT. A total of 89 Pathways sections were sampled, and 108 sections reported data. Among these, 64 were sampled sections that submitted data, and 44 were “bonus” sections that were not sampled but still reported. Enrollment in reporting sections totaled 7,155 students. Footnotes clarify that some sections were sampled for other Core Concepts that also include QCT, and that enrollment totals may include students who were enrolled in or assessed across multiple Pathways courses.
Outcomes Virginia Tech Measured this Reporting Cycle
- Apply the foundational principles of computational or quantitative thinking to frame a question and devise a solution in a particular field of study.
- Evaluate conclusions drawn from or decisions based on quantitative data.
Virginia Tech's Target for this Reporting Cycle
At least 70% of students will be rated as meeting or exceeding competency in this area.
Methods
All undergraduate students are required to participate in the Pathways general education program. As of Fall 2024, Virginia Tech utilizes a sampling methodology for general education assessment that aims to collect data from a subset of course sections that is representative of the general education curriculum. All courses approved for Pathways are part of the sampling pool. Based on an estimated enrollment population for general education course sections of 80,000 each fall and spring semester, along with a confidence level of 99% and a 2% margin of error, approximately 4,000 students should be assessed each semester. Based on the minimum number of students that can be assessed in any one section (i.e., 20), this equates to approximately 200 sections per semester. The number of course sections sampled for each Core Concept is then based on the required number of credit hours that students must complete in each area (i.e., Core Concepts that require students to complete nine credit hours have a greater number of sampled course sections than areas in which six credit hours are required).
When developing a final sample each semester, if a course section was already selected to participate in another Core Concept area, this course section was excluded from selection in other areas. Except for extremely rare cases, if an instructor was already selected during the current semester or a previous semester within the four-semester data collection period, this instructor was not required to participate again. Additionally, large-enrollment course sections from each Core Concept were sampled. Large-enrollment course sections are defined as those having more than 200 students enrolled on average.
Instructors develop their own assessment methodologies based on the content and structure of the course. Students complete the required assessment(s) developed by the instructor teaching the sampled course section. All assessments must be direct measures of student learning. Some possibilities include: written assignments, multiple-choice items, projects, case studies, and artistic creations. Faculty determine what is a developing competence, competent, and advanced competence level of performance on each learning outcome. Rubrics have been developed to guide faculty in this process.
Data and Analysis
Table 2 summarizes competency level results for two Student Learning Outcomes (SLOs) in the QCT area. For SLO 1, which focuses on applying foundational computational or quantitative thinking to frame questions and devise solutions, 103 sections and 6,124 students were included in the analyses. Of these students, 7% (407) demonstrated Developing Competence, 20% (1,251) were rated Competent, and 73% (4,466) demonstrated Advanced Competence. For SLO 2, which focuses on evaluating conclusions or decisions based on quantitative data, 97 sections and 5,071 students were included in the analyses. Of these students, 8% (403) demonstrated Developing Competence, 19% (984) were rated Competent, and 73% (3,684) demonstrated Advanced Competence. A footnote explains that instructors are required to teach and assess a majority of the six QCT SLOs, so the number of sections included in the analyses varies between SLO 1 and SLO 2.
SLO 1: Apply the foundational principles of computational or quantitative thinking to frame a question and devise a solution in a particular field of study.
Table 3 provides a summary of the Pathways sections and student enrollments that reported data and were included in the analyses for SLO 1. A total of 103 Pathways sections reported data. Enrollment across those sections totaled 7,074 students, and 6,124 students were included in the analyses. A footnote notes that enrollment totals may include students who were enrolled in or assessed in multiple Pathways courses.
Figure 1 shows the competency level distribution for SLO 1, which focuses on applying foundational computational or quantitative thinking to frame questions and devise solutions. Based on 6,124 students, 7% (407 students) demonstrated Developing Competence, 20% (1,251 students) were rated Competent, and 73% (4,466 students) demonstrated Advanced Competence.
SLO 2: Evaluate conclusions drawn from or decisions based on quantitative data.
Table 4 summarizes the Pathways sections and student enrollments that reported data and were included in the analyses for SLO 2. A total of 97 Pathways sections reported data. Enrollment across those sections totaled 6,054 students, and 5,071 students were included in the analyses. A footnote notes that these values may include students who were enrolled in or assessed in multiple Pathways courses.
Figure 2 presents the competency level distribution for SLO 2, which focuses on evaluating conclusions drawn from or decisions based on quantitative data. Based on 5,071 students, 8% (403 students) demonstrated Developing Competence, 19% (984 students) were rated Competent, and 73% (3,684 students) demonstrated Advanced Competence.
