NJIT's Perspective on AI Usage in Teaching/Learning

NJIT is a university dedicated to equipping students and instructors with the necessary skills and resources to navigate a changing teaching and learning landscape while staying at the forefront of educational innovation.

AI in Teaching/Learning

The university acknowledges the rapid development of generative artificial intelligence (AI) and its potential impact on education. As a whole, NJIT’s perspective on AI is to foster intellectual development, critical thinking, and to uphold academic integrity standards while taking ethics, data, and privacy concerns seriously. Our perspective is focused on enhancing the learning experience to prepare students to excel in a workforce where AI plays an increasingly significant role. However, the adoption of AI will vary across disciplines and styles of teaching. Therefore, instructors should have autonomy in developing specific policies within their courses, while NJIT offers guidance and resources to foster its ability to remain at the forefront of educational innovation.

NJIT Perspectives

This section refers to the responsible use of AI in alignment with legal regulations, NJIT policy, and end-user awareness. Responsible Use means that these tools are not shortcuts to bypass the learning process but tools to advance it.

  • Copyright: Provides exclusive rights to human authors to protect the work they’ve created for a limited period of time. 

  • Plagiarism: Using content (ideas, words, processes, and results) not written by oneself and sharing it as one’s work is considered plagiarism. Unless cited or permitted by one’s instructor, the university emphasizes this concept of plagiarism. Resources: 

    1. Students: DOS Plagiarism page & the Writing Center

    2. Instructors: Course Requirements and Expectations (Includes syllabus language pertaining to Academic Integrity)

  • AI Bias: The potential for AI systems to exhibit unfair or discriminatory behavior due to flaws in the data used to train them or the algorithms. Some key types of AI bias include:

    1. Training Data Bias: If the data used to train an AI model is biased or unrepresentative of the real-world population, the model may learn and perpetuate those biases. 

    2. Algorithm Bias: The algorithms and machine learning techniques used to develop AI systems can also introduce bias. 

    3. Interaction Bias: AI systems can also exhibit bias when interacting with different user groups. 

    4. Societal Bias: AI systems can inadvertently amplify or reflect existing societal biases and stereotypes in the real world if they are not carefully designed and monitored.

  • AI Misinformation: AI misinformation refers to the dissemination of false or misleading information through the use of AI technologies, which may be spread intentionally to deceive or manipulate individuals, influence public opinion, or undermine trust in information sources. Recommendations for mitigation: 

    1. Read sources cited by AI, instead of just using them. 

    2. Do your research and compare information from multiple sources.

    3. Look for attributes to AI within text and media to check if something was AI generated. 

  • Usage with Citation: Citing your AI tool sources is critical when using AI tools to identify information, especially when paraphrasing content directly from AI. Different citation authorities have varying perspectives on using AI in their fields and how to cite AI:

    1. AI Citation Research Guide: AI Futures Research Guide for information about citing AI-generated content

    2. General Citation Research Guide: Citation Styles Research Guide for guidance about citations in general

  • AI Detection Tools: The university supports using plagiarism detection tools, but not as the sole reason for going against academic integrity, as no AI Detector is 100% accurate. NJIT recommends that instructors first speak with students regarding any potential violations of academic integrity. Further investigations may take place by reaching out to the Dean of Students. NJIT’s knowledge base includes the following information regarding AI detection. 

  • Equity: Similar to various technologies that can be bought, numerous AI tools in the market may be bought by some students but not by others. NJIT is working to increase its library of AI-licensed tools to decrease the equity gap. When opening up the ability to use AI for students, it is recommended to limit this usage to NJIT-licensed tools. 

  • Communication: As requirements vary by course, this information should be addressed in a course’s syllabus. See Course Requirements and Expectations for language you may include in your syllabus regarding the use of AI.

AI Data refers to the information that is used to train, validate, and operate AI systems which can come in various forms such as images, text, audio, video, structured datasets, etc. 

AI algorithms rely heavily on data to learn patterns, make predictions, and perform tasks, so the quality and quantity of the data significantly impact the systems' performance and effectiveness. 

IMPORTANT: When interacting with generative AI applications, these applications may collect, store, use, and sell data for reasons such as business intelligence, personalization, monetization, user experience, competitive advantage, or compliance requirements, etc.

  • Security: While AI is advancing swiftly, NJIT and its community must know what data is transferred to AI and how it is used. Any AI tool licensed university-wide goes through a security and data vetting process within the Information Services and Technology (IST) division. If a department or instructor desires to obtain an AI tool, it is recommended that they touch base with IST at help.njit.edu for assistance in vetting. 
  • Confidential Data: No confidential information should be shared with the AI if it is being trained on the content submitted. This also pertains to students using AI tools. If students are asked to use AI, they will be made aware of what not to do. Possible syllabus language may include: 

This course will ask students to use artificial intelligence (AI). As such, when using the AI, avoid sharing personal information (e.g., full name, email address, or location). It is recommended to turn off features that may collect unnecessary data and delete personal data if possible.

Course pedagogy represents the methods and principles used to design and deliver educational courses to facilitate the teaching and learning experience.The goal of pedagogy is to foster student success in meeting course learning outcomes. 

Course-Specific Policies and Syllabus Language 

Instructors may continue to retain autonomy regarding AI-specific policies in their courses. This section details three pathways that NJIT instructors may take regarding course policy on AI usage for students. Please note that regardless of a course's stance on student use of AI, it is recommended that every instructor inlude their policy in the syllabi, so expectations are clear for students (as they may vary from course to course).

NJIT has provided access to certain AI tools at a university level. Some instructors may ask students to use AI in their courses. For AI that is not available university-wide, please be aware of the equity and data challenges that may be associated with a tool that is desired for instructional use.

Complete Prohibition

  • Possible reasoning for this policy: 

    • Focus on developing foundational skills that are not dependent on AI technologies. 

    • Assess skills based on a student’s own efforts and understanding. 

    • Prioritize human interaction within a course, promoting human engagement with peers and/or instructors. 

    • Limit the ethical concerns in AI usage regarding the course content or data. 

    • Encourage creativity through a student’s own exploration and thinking. 

    • Increase equity in a course, as not all AI tools will be available to all students. 

  • Syllabus Language Example

This course expects students to work without artificial intelligence (AI) assistance in order to better develop their skills in this content area. As such, AI usage is not permitted throughout this course under any circumstance. 

Allowed, with Citation/Acknowledgment

  • Possible reasoning for this policy:

    • Encourage students to analyze and evaluate AI-generated information, including its reliability, accuracy, and relevance. 

    • Use AI as a resource for conducting research to complement their own research efforts. 

    • Inspire students with new ideas and perspectives from AI, allowing them to build on existing knowledge. 

    • Encourage interdisciplinary collaboration by allowing students to reference content in various areas of study. 

    • Prepare students for AI usage as a part of their daily responsibilities in the workforce. 

    • Have students develop a deeper understanding of AI ethical considerations in society and academia. 

  • Syllabus Language Example

While artificial intelligence (AI) is permitted in this course, it is not permitted to be used in the following assignments: X, Y, Z. Additionally, if and when students use AI in this course, the AI must be cited as is shown within the NJIT Library AI citation page for AI. 

Allowed Freely, without Conditions

  • Possible reasoning for this policy:

    • Encourage the exploration of AI technologies with the freedom to discover, innovate, and learn through hands-on experience. 

    • Provide students with autonomy over their usage of AI while allowing them to take ownership of their own learning. 

    • Prepare students to use AI in the real world, as individuals commonly have access to AI and can use it without the need to reference it. 

    • Enable students to experiment, adapt, and stay at the forefront of the evolving AI landscape. 

    • Promote innovation in teaching and learning where AI applications are explored in novel ways. 

    • Encourage students to experiment and explore AI technologies outside the constraints of a classroom environment.  Syllabus Language Example

  • Syllabus Language Example

The usage of artificial intelligence (AI) is permitted in this course and no citation is necessary. 

Learner Interactions

  • Active Learning: Where applicable, NJIT promotes the use of active learning to involve all students in the learning process. Active learning is when students are not passively just listening in the learning process. Rather, they are actively involved (Patino, Ramirez-Montoya, & Buenestado-Fernandez, 2023). NJIT’s Scale-Up room, if available, and the NJIT Active Learning Proposals may be used to foster this active learning initiative. 
  • Adaptive Learning: Based on a learner’s needs, preferences, and performance, this type of learning adapts and provides tailored feedback, pace, and instructional content to enhance student learning. At NJIT, adaptive algorithms may be used to enhance the learning experience. 
  • Human Element: The power of AI is recognized, but it cannot replace human interaction in education. NJIT encourages instructors and departments to increase interactions in their courses, including instructor-student and student-student interactions, through various means, such as smaller class sizes, flipping the classroom, and active learning techniques. 

Professional Development & Support 

  • Continual Advancement: NJIT advocates for development opportunities for instructors to adapt to the changing teaching and learning landscape. The logistics of current pedagogical and technical support are currently being discussed and will be updated here when available. The following options currently exist at NJIT: 
  • Student Support: As instructors will have their own course policies, the requirements of students will vary based on the course. Therefore, students should first work directly with their instructors as a first avenue of support. Students may use the following areas to obtain further assistance: