Jones College of Business IT Services
JCB Faculty Technology Survey Summer 2026
In the 2026 Summer, the Jones College of Business conducted a faculty survey to identify the level of technology use, needs, and other technology-related factors within the college. The results of this survey can offer guidance for decisions related to technology adoption, training, and professional development opportunities at our college. Our goal is to find ways to support our faculty in using technology to better fulfill our educational mission.
The survey had a total of 77 respondents, a 7% decrease in response rate compared to the previous survey conducted in 2022. Below is a summary of the responses. On this page, you will find the survey results and the steps we are taking to address the issues you raised. We will update this page periodically to inform you of the progress of the actions to be taken. We created this page to share the information and to provide full transparency in this process.
Canvas & Instructional Technology
- An overwhelming majority (86%) of faculty/instructors use Canvas. This is a new LMS and reflects initial summer adopters.
- The top used features in Canvas are: Assignments (98%), Modules (98%), Grades (96%), and Announcements (92%).
Followed by Discussion (81%) and Quizzes (81%), Rubrics (57%), Inbox (43%), and Studio (28%). - The instructional approaches used more frequently are: Active Learning (87%), Project-Based Learning (74%), and Experiential Learning (EXL) (64%).
Followed by: Team-Based Learning (53%), Case-Based Learning (51%) and Flipped Classroom (42%). - The top third-party tools integrated with Canvas are Panopto (19.35%), McGraw-Hill Connect (18.71%), Zoom (18.71%), Turnitin (12.9%), Teams (5.81%), Cengage (5.16%), and Pearson Labs (4.52%).
- The most requested Canvas training topics are Course Design (42%), Canvas Studio (42%), SpeedGrader (38%), followed by Quizzes (21%) and Rubrics (19%).
- Software and Tools used in Class: MS Office (87%), Capital IQ (18%), Python/Jupyter (16%), followed by Tableau (14%) and WRDS (14%).
- Canvas satisfaction varies by department, with ISA (3.8/5), MKT (3.7/5), MGMT (3.5/5), ECON (3.5/5), and ACTG (3.1/5).
- External Learning Platforms used in the classroom: McGraw-Hill (68%), LinkedIn Learning (33%), Cengage (18%), Pearson MyLab (14%), and Breakout Learning (7%).
- Main challenges regarding the use of technology
- Our faculty cited a lack of time (66%) and a lack of tech skills (40%) as the main challenges in using technology.
- Lowest satisfaction reported with Audio/microphones, remote recording, and docking station.
AI in Teaching
- The most used AI tools for teaching and course preparation are ChatGPT (84%), Copilot (52%), Grammarly (47%), Gemini (44%), and Claude (42%).
- Faculty reports using AI most often: weekly, followed by a few times each semester, and daily, with monthly and never trailing behind.
- Faculty allows AI for selected assignments (35.48%), integrated throughout the course (19.35%), permission required (17.74%), encouraged (16.13%), required in some assignments (8.06%) and prohibited (3.23%).
- Faculty most often use AI to brainstorm ideas (16%), develop assignments (13%), develop lecture materials (13%), create rubrics (10%), create presentations (9%), and create quizzes/exams (8%).
- AI fluency skills taught: ethical use (57%), evaluating output (45%), fact checking (42%), understanding limitations (42%), foundations (38%), responsible citation (37%), assisted writing (42%), prompt engineering (42%), and understanding bias (42%).
- Assignments allowing AI: oral presentations (43%), in-class assessment (43%), project documentation (40%), reflection papers (31%), proctoring (26%), prompt submission (19%), and peer evaluations (12%).
Followed by: AI statement (1%), acknowledgment (1%), and disclosure (1%). - How to assess learning: presentations (16.89%), class/term projects (12.84%), case analyses (11.49%), analytic projects (8.78%), programming (8.78%), research papers (8.11%), business plans (7.43%), reflections (6.08%), marketing campaigns (6.08%), and capstone (4.05%).
- Biggest concerns: Student overreliance (85%), academic integrity (83%), impact on learning (80%), privacy (47%), hallucinations (45%), copyright (42%), lack of training (42%), assessment challenges (40%), and sustainability/environment (32%).
AI in Research
- 56% of faculty currently use AI in their research, while 19% plan to and 16% don’t.
- Faculty use AI in research mostly for finding articles (76%), literature reviews (58%), brainstorming (56%), summarizing literature (54%), citation assistance (49%), writing/editing (43%), programming (19%), data visualization (17%), survey design (13%), data cleaning (11%), qualitative coding (9%), grant writing (7%) and pre-submission review (1%).
- The most used AI tools for research are ChatGPT (76%), Claude (52%), Copilot (32%), Gemini (28%), Perplexity (16%), NotebookLM (14%), Elicit (8%), Research Rabbit (6%), and Consensus (4%).
- The top barriers to AI use in research are cost (50%), lack of training (33%), and publisher restrictions (31%)
Followed by: IRB concerns (27%), being unsure which tools to use (25%), privacy (22%), and lack of institutional guidance (18%).
The Jones College of Business strives to provide the best IT services and support possible to all our patrons, faculty, staff, and students. This page identifies the main issues raised in the technology survey and action items to address them. We will focus on providing the best service possible within our limitations. Below you will find a list of the top issues and requests, alternatives to address them, and current status as we progress – some items required the coordination with other units such as ITD, MTSU Online, facilities services, etc. Please note that this document is not oriented to provide an exhaustive list of options or solutions. Please don’t hesitate to contact [email protected] if you have any questions.
| Theme | Summary | Faculty Comments | Possible Actions/Options | Status |
|---|---|---|---|---|
| 1. Premium AI Tools and Institutional Subscriptions | Faculty do not want to rely exclusively on free AI services. Claude was mentioned repeatedly, with additional interest in ChatGPT Professional and Copilot Pro. Faculty also want the flexibility to select tools based on teaching or research requirements. | “A subscription to the pro version of Claude.” “AI subscriptions paid by the university AI tools training” “ChatGPT professional/premium” “Claude for education” “MTSU pays for the professional version of AI tools like CLAUDE.” “SPSS, AI, particularly Claude” Subscriptions to CHATGPT and Claude. Training on acceptable use of AI for teaching, including generating materials and in the classroom.” “The following technologies would be helpful: Breakout Learning, Claude Pro, and Copilot Pro. I would like a short video that explains the features of LLMs like Claude; for example, how ot use Cowork.” “The option to use different AI tools” | 1) The university offers the following tools: Grammarly MS Copilot Chat MS M365 Copilot (paid) 2) The first 40 faculty who register and complete the full workshop series will be eligible to receive a one-year license for an MTSU-approved AI platform, subject to funding availability and MTSU ITD review and approval. Additional details, including the selected platform, will be provided as they become available.” | ✅Dean’s Office will fund AI licenses |
| 2. AI Training, Prompting, and Foundational Skills AI Policy, Ethics, Governance, and Oversight | Faculty experience ranges from novice to technically advanced. They want practical instruction tied to real work, especially course development and research. They specifically reject passive, lecture-heavy workshops and simulated exercises. | “AI subscriptions paid by the university, AI tools training” “I am too much of a novice (looking over the list from a previous question) to know what I could benefit from using beyond better use of AI.” “None for teaching so far. But I would appreciate some workshops for using AI, such as LLM, in the research.” “Probably AI, Canvas training that allows more interaction, not being lectured at. I want to work on my courses, not pretend I’m working on a course – feels like wasted time.” “The following technologies would be helpful: Breakout Learning, Claude Pro, and Copilot Pro. I would like a short video that explains the features of LLMs like Claude; for example, how ot use Cowork.” “Training in better prompt engineering.” “Using AI in instruction to accelerate research” “agentic AI training; training on AI governance and AI oversight” “AI and policy training.” | 1) The JCB Dean’s Office, in collaboration with the IT Resources Director, the JCB Faculty Development Committee, and the AI Community of Practice, will offer an AI in Business Workshop Series. Four Sessions: Fall 2026 Series: a) AI Tools & Responsible Use (09/24 & 25) b) AI in Teaching & Assessment (10/23 & 24) Spring 2027 Series: c) Effective T&P + Annual Review with AI when useful d) AI in Research The workshops will be: Hands-on & Peer-led Practical and application-oriented 2) JCB Tech Tips will feature monthly AI tips 3) JCB IT Resources will publish information on our website and Canvas JCB Learning Community | In Progress ✅Completed Session I |
| Canvas Training: Studio, SpeedGrader, Rubrics Gradebook Basic Functionality Importing D2L to Canvas & import D2L Quizzes | 4) The JCB IT Resources Director will offer Canvas Q&A Sessions, including Studio, SpeedGrader, and Rubrics. | ✅JCB Tech Tip: Canvas Studio completed. | ||
| 3. AI in Teaching and Assessment | Faculty want concrete examples from disciplines and colleagues, not only general tool demonstrations. They want help integrating AI into instruction while maintaining meaningful learning | “Examples and specific uses of AI in the classroom; how to verify that students are learning the content versus copying and pasting content without understanding it.” “Presentations by faculty who are using it successfully.” Training on acceptable use of AI for teaching, including generating materials and in the classroom.” Tools and teaching faculty to better determine when AI is used by students in assignments, etc., where AI was not permitted. Turnitin is good, but telling a student AI was used when the student states otherwise can be a difficult issue to resolve.” | The JCB Dean’s Office, in collaboration with the IT Resources Director, the JCB Faculty Development Committee, and the AI Community of Practice, will offer an AI Signature Workshop Series. AI in Teaching & Assessment Workshop | In Progress |
| 4. AI in Research | Faculty are concerned about learning verification, unauthorized AI use, disputes over AI detection results, online assessment security, and the limitations of current proctoring practices. Faculty need clarity about what is acceptable, what data may be entered into AI tools, how AI use should be disclosed, and how ethical considerations differ between teaching and research. | “Using AI in instruction to accelerate research” “Training on Claude Code would be beneficial; training on ethics in AI (in terms of its use in research and teaching separately); training on methods of assessment in asynchronous online classes to mitigate students’ ability to use AI” “Better proctoring services.” | The JCB Dean’s Office, in collaboration with the IT Resources Director, the JCB Faculty Development Committee, and the AI Community of Practice, will offer an AI Signature Workshop Series. * AI in Teaching & Assessment Workshop * AI in Research Workshop ITD is piloting Respondus LockDown Browser | In Progress |
| Last Update | 09/25/2026 |
| Question | Answer/ | Resources |
|---|---|---|
| AI in Business Session 1: AI Tools & Responsible Use (Fall 2026) | Agenda Summarizing Recording | |
| AI in Business Session 2: AI in Teaching & Assessment (Fall 2026) | ||
| AI in Business Session 3: Effective T&P and Annual Review (Spring 2027) | ||
| AI in Business Session 4: AI in Research (Spring 2027) | ||
| Where to learn the basics of AI, guidelines, policies, AI and Ethics | AI in Higher Education Canvas Course, by Tim Oneal, PhD. Open to all faculty, enroll using this link: https://mtsu.instructure.com/enroll/X83H6N Middle Tennessee State University (MTSU) enforces artificial intelligence ethics primarily through MTSU Policy 323, which governs the instructional and assignment use of Generative AI (GAI) Lecture Video Series: Module 1 Section 1 – Understanding Generative AI Module 1 Section 2 – Practical Uses of AI in Online Teaching Module 1 Section 3 – Recognizing the Risks Module 2 Section 1 – Understanding MTSU Policy 323 Module 2 Section 2 – Translating Policy into Course -Level Standards Module 2 Section 3 – Ethical Responsibilities Module 3 Section 1 – AI as a Teaching Workflow Tool Module 3 Section 2 – Creating Discussion Prompts Module 3 Section 3 – AI for Accessibility & Instructor Presence (RSI) Module 4 Section 1 – From Detection to Design Module 4 Section 2 – Designing AI Resilient Assignments Module 4 Section 3 – Rethinking Exams & Assessment Strategy Module 5 Section 1 – AI in the Research Process Module 5 Section 2 – The Hallucination Problem & Verification Module 5 Section 3 – Citation, Transparency, & Responsible Scholarship | Scholars Are Divided Over How Much AI Use Is Acceptable, Chronicle of Higher Education, Katherine Mangan and Shea Vance. |
This page will be periodically updated.
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