Review Assessment Report

Part 1: Contact & Program Identification

Report Year and Contact Information
Academic Year	Modified By	Date Modified
2021-2022	nholtschulte@cnm.edu	2022-10-18T15:55:50.187Z

School	Name of Program	Courses
BIT	Computer Science Degree	BCIS 1110,COMM 1130,CSCI 1152,CSCI 2201,CSCI 2251,MATH 1510,MATH 1520

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
During the 2022-2023 school year we hired a full time CS instructor, Guadalupe Torres. CSCI 1152 underwent a review in conjunction with Instructional Support. BHT is looking at course shells and considering separate course templates for 15 week versus 12 week courses. Naming conventions for CS and CIS courses are being discussed in collaboration with representatives from educational institutions across the state in order to improve clarity for students and simplify transfer of credits between institutions. Changes in technology as well as the need to support online and in-person students continues to be a challenge and a significant mental and time burden on faculty. Making time to clarify course learning outcomes, craft assessments that effectively measure such outcomes, and compile such data has fallen by the wayside and is going to be re-emphasized in the near future.

Provide a high level review of the program to include highlights, successes, challenges, significant changes, and significant resources needed to support the program

During the 2022-2023 school year we hired a full time CS instructor, Guadalupe Torres. CSCI 1152 underwent a review in conjunction with Instructional Support. BHT is looking at course shells and considering separate course templates for 15 week versus 12 week courses. Naming conventions for CS and CIS courses are being discussed in collaboration with representatives from educational institutions across the state in order to improve clarity for students and simplify transfer of credits between institutions. Changes in technology as well as the need to support online and in-person students continues to be a challenge and a significant mental and time burden on faculty. Making time to clarify course learning outcomes, craft assessments that effectively measure such outcomes, and compile such data has fallen by the wayside and is going to be re-emphasized in the near future.

Part 3: Data Review

	2019-2020	2020-2021	2021-2022
Annual number of graduate awards is greater than 10	28	25	27
Number of declared majors	666	656	627
Average Class Size	23.1	22.1	20.8
Annual Average Class withdrawal rate is 30% or below (SAGE 35%)	15%	14%	12%
Annual C-Pass rate for coursework is 60% or above	71%	67%	67%
Average class fill rate at 60% or above capacity within a term or over a year	79%	77%	74%
Graduate Transfer to 4-year Schools	57%	n/a	n/a
Full-time Faculty Coverage by Section	50%	60%	22%

Summarize how your program met or did not meet the target measures based on the data above
Average class fill rate has been consistently above 60% for the past three school years (2019 - 2022) and is expected to continue above 60%. Other metrics have similarly been met. Full-time Faculty Coverage by Section dropped to 35% in 2021-2022, but this number should be back up again now that the full-time faculty vacancy has been filled. I'm a little confused by this form because one of the targets listed is "Annual retention rate is 70% or above (SAGE 65%)" but that information is not provided in the above data unless it's the inverse of "Annual Average Class withdrawal rate is 30% or below (SAGE 35%)", in which case the target has been met. Though on this note, it would be great to improve retention as the average is not spread evenly across all classes (anecdotally) with a lot more students dropping the harder core Java courses 1152 and 2251 compared to courses such as Netlogo 1108 and Matlab 1153.

Summarize how your program met or did not meet the target measures based on the data above

Average class fill rate has been consistently above 60% for the past three school years (2019 - 2022) and is expected to continue above 60%. Other metrics have similarly been met. Full-time Faculty Coverage by Section dropped to 35% in 2021-2022, but this number should be back up again now that the full-time faculty vacancy has been filled. I'm a little confused by this form because one of the targets listed is "Annual retention rate is 70% or above (SAGE 65%)" but that information is not provided in the above data unless it's the inverse of "Annual Average Class withdrawal rate is 30% or below (SAGE 35%)", in which case the target has been met. Though on this note, it would be great to improve retention as the average is not spread evenly across all classes (anecdotally) with a lot more students dropping the harder core Java courses 1152 and 2251 compared to courses such as Netlogo 1108 and Matlab 1153.

Part 4: Program Learning Outcome Analysis

Learning Outcome	Population or Course(s) Assessed	Description	Summary of Assessment Results
5. Able to solve problem cross network and platform via both lower and higher level API.	CSCI 2251
7. Apply algorithms to problems involving complex computation, compare and analyze different approaches of computation problems.	CSCI 2201
3. Apply appropriate data structure, access of data, operate data stored inboth internal and external computation devices.	CSCI 1152/1151
8. Apply software package (such as MATLAB) to solve computation problems.	CSCI 1153
6. Apply the principles of a variety computation theories and techniques to solve problems.	CSCI 2201
4. Demonstrate an understanding of algorithm, problem solving by creating algorithmic solutions, and provide practical implementations.	CSCI 1152/1151
4. Demonstrate an understanding of algorithm, problem solving by creating algorithmic solutions, and provide practical implementations.	CSCI 2251
2. Develop moderate complex computer programs using programming languages.	CSCI 1152/1151
1. Develop the knowledge of computational thinking skills and build the fundamental structures for agent-based computer modeling.	CSCI 1108 – CS For All: Introduction to Computer Modeling
9. Write programs using predefined functions and procedures, conditional statements, control structures, matrix computations, and graphing and plotting (using MATLAB).	CSCI 1153

Interpretation of Assessment findings
All three of these skills are taught and assessed, some more directly than others. Not included on this list (or at least I'm not clear where they fit into this trio of categories) are formation of correct mental models (critical thinking?) and basic syntax (info and literacy?) which are two major categories I perceive when considering teaching and assessment. Perhaps my most significant interpretation is that assessment has become misaligned with course outcomes such that hard numbers relating to these outcomes are not available. I personally have been scrambling to modify or recreate assessments (and lectures) throughout all my courses to improve student outcomes along my own metrics (for instance providing opportunities to receive feedback over the course of a large project rather than a harsh one-shot grade at the due date) and I have not been mindful of alignment with measured outcomes. In order to gather meaningful data, this will have to change.

Interpretation of Assessment findings

All three of these skills are taught and assessed, some more directly than others. Not included on this list (or at least I'm not clear where they fit into this trio of categories) are formation of correct mental models (critical thinking?) and basic syntax (info and literacy?) which are two major categories I perceive when considering teaching and assessment. Perhaps my most significant interpretation is that assessment has become misaligned with course outcomes such that hard numbers relating to these outcomes are not available. I personally have been scrambling to modify or recreate assessments (and lectures) throughout all my courses to improve student outcomes along my own metrics (for instance providing opportunities to receive feedback over the course of a large project rather than a harsh one-shot grade at the due date) and I have not been mindful of alignment with measured outcomes. In order to gather meaningful data, this will have to change.

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	Provide more support and opportunities for students with inadequate computing background. Opportunities to practice syntax separate from broader computer program construction.	Retention and the C-passing rate
2021-2022	Create a direct connection between assessments and learning outcomes that we wish to measure.	The motivation is a lack of data on desired learning outcomes.
2021-2022

Please select all of the following that characterize the types of changes described in the above action plan

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