When the Department of Mathematics and Statistics at Cleveland State University was considering the potential for adaptive learning to affect pass rates in its introductory Mathematics courses, they didn’t have to look far. By digging into the courseware they had already been using for years to deliver lessons and practice activities, they were able to successfully launch a pilot that showed almost immediate results.

In Fall 2019, Mathematics faculty at Cleveland State University began an effort to use dashboard data from the software — ALEKS — to make mid-stream adjustments in assignments, quizzes, and tests. In doing so, the department achieved its goal of normalizing pass rates at above 75 percent for several sections of Precalculus courses.

And they expect to help even more students succeed by using data from adaptive learning software to identify where courses can be refined in future semesters.

#### A “mini-run” to test the dashboard data

Because the Cleveland State University Mathematics and Statistics Department was already thinking about how to get more out of its adaptive learning software, when the Association of Public and Land-grant Universities (APLU) offered support and expertise, instructors were ready to engage in a pilot.

They expanded their previous experience with ALEKS, an artificial intelligence, web-based program and learning system that supplies course content for several introductory college courses including math, chemistry, and business. Before Spring 2019, the Mathematics and Statistics Department rarely used the data from ALEKS to identify areas where individual classes were struggling to make adjustments during the semester.

Math faculty used the last four weeks of the Spring 2019 semester to conduct a “mini-run” on their MTH 95-Applied Algebra, MTH 167-Precalculus I (College Algebra), and MTH 168-Precalculus II (Trigonometry) courses. Instructors for those courses practiced pulling and reviewing data and adjusting assignments to make sure the process would work.

Juan Amador, Interim Director, Operation STEM, Louis Stokes Alliances for Minority Participation, Department of Mathematics and Statistics, at Cleveland State University says, “Using the ALEKS dashboard was just amazing.” The way it revealed topics that students were struggling with and differences between sections or student groups convinced the department they were ready to fully implement adaptive learning for the Fall 2019 semester.

*Related reading: **Using Data from Adaptive Learning to Help Underserved Students*

#### Applying dashboard data to make mid-stream adjustments

Before using ALEKS data, the Precalculus Coordinator would construct homework assignments and quizzes for the semester by randomly selecting problems from the software’s question bank.

In Fall 2019, however, Cleveland State University’s Mathematics and Statistics Department began adjusting homework problems weekly as data showed where students were struggling. The pilot project focused on three courses: MTH 165-Intensive Precalculus I (a newly implemented co-requisite course consisting of all topics learned in MTH 95 and MTH 167), MTH 167, and MTH 168.

Instructors used the ALEKS dashboard data from those courses to evaluate learning within different course sections and among specific student groups to influence curricular decisions. During the Fall 2019 semester, for all three courses, the following steps were carried out each week:

- Sunday through Thursday, students worked in ALEKS on an objective consisting of practice problems on 14 to 18 specific topics.
- Friday morning, the Precalculus Coordinator used dashboard data to identify four of the “most missed” homework problems of each course section.
- They then combined those homework problems with two other review problems covering concepts necessary to master the topics students were struggling with. This six-problem homework assignment was posted Friday morning in ALEKS. (This included both online and written work.)
- Monday morning, instructors collected the written homework for review and identified two of the six written homework problems as “most missed” using dashboard data. The two “most missed” problems were presented on a pencil and paper quiz every Wednesday.

Therefore, each week during the semester, six sections of Precalculus courses, totaling 160 students, cemented math concepts through the use of adaptive learning: analyzing dashboard data and using it to provide additional reinforcement and to adjust homework and quizzes to respond to “most missed” problems.

Instructors began to respond quickly to adjust their assignments and quizzes that narrowed those learning gaps. For example, “Let’s say our current objective was focused on graphing sine and cosine functions,” Amador says. “Before class, the instructor would access the ALEKS data and notice the poor completion rate and the number of failed attempts for certain topics.”

Knowing this, instructors would provide additional instruction time on the topic in the next class meeting. This often led to improved completion rates in the next objectives, homework problem sets and quizzes — and ultimately to increased completion rates of the course at the end of the semester.

*Related reading: **What Are Gateway Courses and Why Do They Matter to Equity in Higher Ed?*

#### Results

Cleveland State University found the results of using dashboard data to inform mid-semester adjustments were encouraging. Although COVID-19 impacted pass rates for courses in the Spring 2020 semester, the Mathematics and Statistics Department did see positive pass rates for all three Precalculus courses in the Fall 2019 semester.

- The newly implemented MTH 165 course measured pass rates of 81 percent at the end of the Fall 2019 semester.
- The new MTH 167-Precalculus I: College Algebra and MTH 168- Precalculus II: Trigonometry measured pass rates of 80 percent at the end of the Fall 2019 semester.

Amador says you can see finite differences among the different sections. He says, “Historically, there were always topics we know were challenging, but with dashboard data, you could see more details.”

Not only can instructors drill down to specific section levels to tailor and adjust assignments, quizzes, and tests, but they can drill down to the student level. They can identify a struggling student who needs additional support. And they’re using that data to reach out and refer them to resources they need to succeed.

Students like using the adaptive courseware because it’s more interactive. In ALEKS, when a student is doing homework and doesn’t understand a concept, they can ask the software to show practice activities that reinforce the concept.

Students also appreciate the initial assessment they take at the beginning of the course. For example, if mastery of 200 topics is necessary to succeed in Math 167 – Precalculus I – College Algebra course and an individual student has previously mastered 50 of those topics according to the initial assessment, the software will prioritize the 150 remaining topics and tailor them in the practice activities for that individual.

#### Continuous improvement

Through testing, refinement, and evaluation, Math faculty at Cleveland State University continue to use the data dashboard across the multiple sections of MTH 165 – Intensive Precalculus, MTH 167 Precalculus I, and MTH 168 Precalculus II.

Next they plan to make informed course-level revisions using the data from the adaptive learning software. For example, the data in MTH 167 – Precalculus I suggests that students will benefit from a small number of additional prerequisite remedial topics, such as adding fractions or converting miles per hour to inches per second. Amador says these topics will aid student understanding of challenging topics later in the semester that the ALEKS data is showing as stumbling blocks.

Then, at the end of the Fall 2020 semester, Amador expects the Math faculty at Cleveland State University to go through the same process of evaluating the results, refining their use of the data, and making additional revisions to their courses to improve student learning and retention of concepts.

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