Review Assessment Report
Part 1: Contact & Program Identification
| Report Year and Contact Information | ||
|---|---|---|
| Academic Year | Modified By | Date Modified |
| 2021-2022 | [email protected] | 2022-10-14T21:37:24.707Z |
| School | Name of Program | Courses |
|---|---|---|
| BIT | Artificial Intelligence & Machine Learning AAS | None |
Part 2: Program Summary
| Provide a high level review of the program to include highlights, successes, challenges, significant changes, and significant resources needed to support the program |
|---|
Artificial intelligence and machine learning are new evolving disciplines. The AIML certificate was added to the 2021-2022 catalog and the AAS degree added in 2022-2023. We have offered 2 courses, AIML 1010 Introduction to Artificial Intelligence and AIML 2010 Advanced Artificial Intelligence. New course to be offered soon include AIML 2110 Deep Learning, and AIML 2120 Natural Language Processing. |
Part 3: Data Review
| 2019-2020 | 2020-2021 | 2021-2022 | |
|---|---|---|---|
| Annual number of graduate awards is greater than 10 | 0 | 0 | 0 |
| Number of declared majors | 0 | 0 | 0 |
| Average Class Size | n/a | n/a | n/a |
| Annual Average Class withdrawal rate is 30% or below (SAGE 35%) | n/a | n/a | n/a |
| Annual C-Pass rate for coursework is 60% or above | n/a | n/a | n/a |
| Average class fill rate at 60% or above capacity within a term or over a year | n/a | n/a | n/a |
| Graduate Transfer to 4-year Schools | n/a | n/a | n/a |
| Full-time Faculty Coverage by Section | n/a | n/a | n/a |
| Summarize how your program met or did not meet the target measures based on the data above |
|---|
We are a new program in the 2022-2023 catalog. |
Part 4: Program Learning Outcome Analysis
| Learning Outcome | Population or Course(s) Assessed | Description | Summary of Assessment Results |
|---|---|---|---|
| 3. Apply statistical analysis and machine learning algorithms to predict usefulness of artificial intelligence (AI) programming solutions. | AIML 2110,
AIML 2120 | ||
| 5. Evaluate issues of bias, culture, environment, ethics, regulations, and professional expectations in the field of artificial intelligence (AI) and machine learning. | AIML 1010 |
| Interpretation of Assessment findings |
|---|
Over 70% of AIML 1010 students score above 70% on bias, culture, environment, ethics, regulations, and professional expectations assignments in AIML 1010. The advanced classes, AIML 2110 and AIML 2120 will be offered during the next year. We expect continued revision of the curriculum during the first years of the program. |
Part 5: Additional Action Plan in Support of Student Learning (If Appropriate)
| Upcoming Year | Changes Planned for the upcoming year | Data Motivating this change |
|---|---|---|
| 2021-2022 | ||
| 2021-2022 | ||
| 2021-2022 |