Teaching with Technology

It would be hard to imagine higher education in the twenty-first century without educational technology, online learning, and, increasingly, artificial intelligence (AI). While technological tools and systems help us design, develop, and deliver learning experiences, they might not always align with our pedagogical goals. For example, a learning management system (LMS) like Blackboard or Canvas might provide an efficient process for collecting assignments and offering timely feedback (e.g., via the rubric tool) but the top-down structure of LMS architecture might not support student-centered pedagogical practices like ungrading or collaborative rubric design. Similarly, while generative AI applications open new possibilities for individualized learning or skill augmentation they also create significant challenges in the areas of academic honesty, foundational skill development, or equity. Incorporating new technologies in the classroom (virtual or physical) can be exciting and productive. Nevertheless, selecting technologies that support our learning goals and pedagogical values requires a significant amount of intentional design and iteration, including ongoing communication with students.

Technology Enhanced Instruction

Digital technology has become an indispensable part of modern education. Tech tools help us organize content, engage students, assess progress, deliver feedback, and support individual learning needs. The key to successfully integrating teaching technology in any course is intentionality: carefully considering course learning goals and selecting the tools that will help meet those goals, rather than adapting tech tools simply because they are available or under the pressure of technological determinism. For instance, if we hope to increase student engagement in a course, an interactive polling tool or discussion platform might help advance this objective. Even then, it’s important to balance potential benefits with trade-offs like the anticipated learning curve. Will the time and effort required to learn and implement a new tool be justified by improvements in student engagement? Or can the learning goal be better supported in other ways? In a time when rapid advances in technology are challenging to keep up with, focusing on learning goals and carefully assessing trade-offs can help instructors select technologies most likely to support student learning, inside and outside the classroom. 

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Hybrid and Online Pedagogy

Over the past several decades, online learning has become an essential course modality in higher education. Its popularity is largely driven by flexibility: students can access course materials, participate in discussions, and complete assignments without having to be physically present on campus. Most online courses fall into three categories: synchronous, asynchronous, or hybrid. Synchronous learning involves online class meetings conducted during scheduled times. In asynchronous online courses, students access course materials and assignments on their own, usually following a week-by-week schedule. Hybrid learning typically refers to courses that pair reduced in-person class meeting times with increased online coursework (at Drexel University, hybrid learning consists of in-person classes that meet at established times, as well as online classes that may be either synchronous or asynchronous). 

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Generative Artificial Intelligence (GAI) and Teaching

As generative artificial intelligence continues to transform higher education, students are looking for guidance on effective and ethical uses of AI tools in their coursework and professional lives. The relative novelty and rapid development of generative AI offers academic instructors an opportunity to model lifelong learning and create community norms in collaboration with students. While the impacts of generative AI will differ from discipline to discipline, instructors in all disciplines will need to grapple with the pedagogical implications of the AI revolution. We can do this through: (1) establishing and communicating transparent guidelines; (2) promoting critical AI literacy; (3) addressing academic integrity; (4) redesigning learning experiences and assignments; and, if applicable, (5) leveraging AI for individualized learning.