Book Review: Teaching with AI - A Practical Guide to a New Era of Human Learning

This week's review is on Teaching with AI - A Practical Guide to a New Era of Human Learning by José Antonio Bowen and C. Edward Watson.

A book which states its aim clearly - focusing on the how, not necessarily the why or why not of using AI in teaching. Bowen and Watson present a brief overview on what AI is, before proceeding to Teaching (which includes a discussion of cheating, policies, and quality) and Learning (feedback, assessments, writing). The first section is largely the common language used to introduce AI, so this review will focus on the latter two sections and specific advice.

Where I think Bowen and Watson provide the most insight is in noticing the way AI has set a new standard for work. This is not to say that AI-generated work is of a high quality - but instead to point out that such work is now the bar that humans must surpass to add value: "No one is going to hire a student who can only do C work if an AI can do it more cheaply. We will need to define what 'better than AI' work looks like" (location 128). This challenge lies at the heart of their approach - one centered more on work-readiness and technical skill than a deep consideration of the purpose and method of education. "AI is going to change every job" (458) so Bowen and Watson say we must move forward.

In their guide to prompting, the duo consider the importance of "problem formation":

Oguz Acar calls this “problem formation” or specifically the ability to “identify, analyze, and delineate problems” (Acar, 2023). Acar further breaks this down into four parts: problem diagnosis, decomposition, reframing, and constraint design. These four parts resemble the first parts of innovation processes (like design thinking). Innovation processes always start with insight or diagnosis: What does the user really want to do? What are the barriers to success? For whom is this a problem? This is sometimes called the “empathy” phase, and it is followed by defining (or redefining) the problem.

They offer tips on promoting creativity in response but assure us that "the goal is not to have AI do the thinking, but to have a dialogue that helps you think" (833). Their approach to grade setting is to set the "AI-Level 50% = F. Another way to do this is to examine the AI responses to your assignment prompts and describe those answers as the new F work" (1922). Therefore, "The question as you grade may be: In what ways has the student moved above and beyond what AI produced for them" (1928) with a focus on content rather than grammar or a serviceable outline, two things AI and spellcheckers now provide effortlessly" (1960). This is a call for higher standards and the incorporation of AI in the classroom.

Professors and teachers should work through AI policies together (1707):

First, make sure there is agreement about why their learning this semester is important and relevant. Then discuss why integrity is valuable and how it can help us achieve those learning goals. If the why is clear, students will be more motivated to work out a set of equitable policies. This will also be an opportunity to discuss what AI can and can’t do and make sure everyone has access and some basic understanding of how AI is changing learning and work.

This will establish purpose and context for AI within the course, pushing students to develop their views on trust and integrity. And, more importantly, provide an opportunity for professors to ensure that motivation is aligned with the principles of "I care," "I can," and "I mater." (2332).

The book continues to highlight specific examples and methods that professors can use to incorporate AI. These take the format of very simple ideas, example prompts, and outlined scenarios; along with tools for particular usage:

Asking an AI to be the facilitator or team coach can improve teamwork. There are already Zoom meeting bots that let you know when you are hogging the floor (Chen, 2023). Here are some easy ways an AI could support a team project:

PROMPT

• Act as our team coach and prompt us with questions to discuss how could learn about our collective strengths and work together as an effective team.

• Provide guidance that will help us ensure that all team members contribute equally to this project.

• Propose guidelines for how we should work on this team project. (There is a longer discussion of this in Mollick & Mollick, 2023, September 25).

• Outline the steps and timeline for completing this project.

• Create a two-week project management grid for a team of four to complete this research project.

• Different members of our team want to proceed in different directions on this project. Read the individual proposals and provide a summary of where they overlap and where they do not. Read the assignment instructions, and provide a neutral compromise for how we can move forward.

• Here are the individual ideas about the project. Collate these into a shared plan.

• Examine all of our group materials and list how much each has contributed from greatest to least. Whose ideas might need more voice?

• Help us ensure that all team members contribute equally to this project.

Helpful guides to implementation are a must - especially for professors for whom pedagogy takes a back seat to research and service. For my purposes, I found the broader thoughts here - at the collegiate level - fascinating:

It’s conceivable that one day everyone will assume that all work is AI-assisted, in the same way that we assume all writing has now been through software spelling and grammar checking. We don’t insist that students use a dictionary to check spelling, and we don’t know or care if our favorite author wrote on a typewriter or a computer.

It would be intriguing to pursue this line of thought down to what it means for elementary and secondary education - the elimination of those skills or their deeper necessity as a basis to move beyond "C-level" AI slop?

Teaching with AI - A Practical Guide to a New Era of Human Learning by José Antonio Bowen and C. Edward Watson.

Rating: 4/5 Stars

Good For: Those looking for practical tips at using AI, especially at the collegiate levels.

Best nugget: AI is the baseline - what value can and do humans add to written work?

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