Review Assessment Report
Part 1: Contact & Program Identification
Report Year and Contact Information | ||
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Academic Year | Modified By | Date Modified |
2022-2023 | [email protected] | 2023-10-23T19:56:27.129Z |
School | Name of Program | Courses |
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BIT | Artificial Intelligence and Machine Learning Certificate | 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 |
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This is a new program. We have no graduates as of yet. We have multiple sections of the introductory course. Some students continue with AIML 2010. We are introducing two follow on classes: AIML 2110 and AIML2120. We anticipate our first graduates in Spring term 2024. |
Part 3: Data Review
2020-2021 | 2021-2022 | 2022-2023 | |
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Annual number of graduate awards is greater than 10 | 0 | 2 | 3 |
Number of declared majors | 0 | 22 | 21 |
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 |
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There are 21 students in the progam
There is no other data to compare yet.
Data will be evaluted in the next cycle. |
Part 4: Program Learning Outcome Analysis
Learning Outcome | Population or Course(s) Assessed | Description | Summary of Assessment Results |
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1. Apply common artificial intelligence (AI) concepts and methodologies for analysis and decision making. | AIML 2010 | ||
2. Apply artificial intelligence (AI) project development and machine learning life cycle to address social and business issues, opportunities, and problems. | AIML 1010 | ||
4. Use appropriate programming languages to implement artificial intelligence (AI) solutions. | AIML 1010,
AIML 2010 | ||
5. Evaluate issues of bias, culture, environment, ethics, regulations, and professional expectations in the field of artificial intelligence (AI) and machine learning. | AIML 1010 | ||
1. Apply common artificial intelligence (AI) concepts and methodologies for analysis and decision making. | AIML 2010 |
Interpretation of Assessment findings |
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This is brand new program. There are no findings to interpret because there were only 2 courses were offered over the past year therefore there are no assesment values.
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Part 5: Additional Action Plan in Support of Student Learning (If Appropriate)
Upcoming Year | Changes Planned for the upcoming year | Data Motivating this change |
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2022-2023 | Two new courses will be added to the program - Natural Language Processing and Deep Learning AIML 2010 and AIML 2020 | There was a revision this cycle. |
2022-2023 | ||
2022-2023 |