Teaching Identities and the Learning Sciences: Questions of Research to Practice
Concurrent Session 5
Having gained prominence in recent decades, the learning sciences represent themselves as a timely theoretical initiative in online education. What ideas are most important? How can we tell what is most effective in practice? Can the potential for application of the learning sciences strengthen the reputation of online teaching?
This “Conversation, Not Presentation” falls within the conference track on “Process, Problems, and Practices.” It addresses the challenge of faculty resistance to technological innovation in course design and teaching, or the prospects for bringing ideas from the learning sciences into instruction. For explanatory purposes, this proposal presents an extensive rationale for the timeliness of the subject. It will be condensed considerably in presenting it in favor of making the most of the conversational nature of the session.
Many professors are unconvinced that technology necessarily contributes to student learning. The online curriculum is now well established. But, as surveys show, there is also a persistent lag in faculty enthusiasm for technology in teaching, whatever the signs of its effectiveness from recent work in the learning sciences, an interdisciplinary and empirically oriented research enterprise that has had only a limited impact on the faculty.
Of course, proponents of technology in teaching can say that its effects are only as good as any professor’s understanding of learning allows it to be, or whether they are “innovation ready.” Recent studies seeking to advance knowledge of the learning sciences reflect optimism about faculty interest and adaptability. For example, cognitive psychologist Michelle Miller’s Minds Online: Teaching Effectively with Technology (2014) counts on the faculty’s “drive to innovate.” By using technology informed by learning science, she and her Northern Arizona University colleagues could “do things that [I] knew were beneficial to students, but had never managed to consistently carry out before.”
We are familiar with manifestos for academic transformation, institutional initiatives championing pedagogical reform, and start-up driven models of automated teaching that depend on images of faculty work constrained by habit and indifference to innovation. Proponents of an increased role for the learning sciences in course design and teaching, like Miller, take a different view, focusing, at a suitable scale, on what the operations of the brain mean for how we can teach. Such lessons have been codified in allied work (e.g., Peter Brown, Henry Roediger, and Mark McDaniel, Make it Stick: The Science of Successful Learning (2014), James Lang, Small Teaching: Everyday Lessons from the Science of Learning (2016), and Flower Darby with James Lang, Small Teaching Online: Applying Learning Science in Online Classes ).
Miller’s approach focuses on attention, memory, thinking, motivation, and the cognitive impact of multimedia. She explains the mental processes in each and how what we are learning about the brain’s structure and operations can guide us to effective teaching, online and in hybrid formats. She sees the learning sciences and technology as natural allies but with admirable caution: “I don’t believe that instructional technology promotes learning by its mere presence. Nor does it let us evade some of the apparently immutable truths about how we learn—especially the fact that learning requires focused attention, effortful practice, and motivation. Rather, what technology allows us to do is amplify and expand the repertoire of techniques that effective teachers use to elicit the attention, effort, and engagement that are the bases of learning.”
For Miller, the learning sciences offer permanent improvements in making the most out of technology: “With knowledge of which types of [scientific] approaches have proven effective in actual uses, you will be empowered to make more powerful design choices and to innovate after today’s learning management systems, applications, and gadgets du jour are long gone.” Miller presents herself as a scholar/teacher speaking to colleagues, conveying friendly classroom advice. The goal is “cognitive optimization.” She is decidedly practical and refrains from what some call the evangelical postsecondary discourse. Her aim is to dislodge common cognitive assumptions made by professors, or what is behind their instructional habits.
Such habits are the subject of a competing view of the prospects for moving from research in the learning sciences to instructional practices. Thus, a recent study of the uses of the technology in course design and teaching extends our knowledge of why the faculty often resists instructional innovation, including what represents findings of the learning sciences. The authors, historian of science Joel Smith and anthropologist Lauren Herckis at IT leader Carnegie-Mellon University, say this to introduce their work, which appeared as an extensive CMU report in mid-2018: “Many who have worked in the field of technology enhanced learning over the last 30 years have experienced a frustrating dichotomy. On the one hand, the increasing collaborations among faculty content experts, learning scientists, and technologies have produced significant innovations in instruction with measurable improvements in learning. On the other hand, many (if not most) of these innovations have relatively short lives and seldom propagate beyond the research, development, and initial implementation stages” (“Understanding and Overcoming Institutional Roadblocks to the Adoption and Use of Technology-Enhanced Learning Resources in Higher Education”).
The CMU scholars, both with considerable experience in course design and faculty development, brought a novel approach (reflected in their academic disciplines) to the problem of building and maintaining an institutional culture that welcomes technological innovation in teaching. The ambitious ethnographic and interview study of teaching at CMU revealed several “roadblocks” to instructional innovation, including problems of poorly coordinated collaboration and miscommunications, lack of a “champion” for one or another innovation to guide experimentation and implementation, risk-averse teaching strategies and anxiety about evaluation, and difficulties in aligning the needs and interests of faculty members in different disciplines and at different points in their careers with institutional resources (e.g., teaching and learning centers).
The presentation will feature what may be the deepest “roadblock,” or the durability of teaching “identities” (some may prefer the term “dispositions” to the theoretically dense “identities”). Thus, the CMU report found that the faculty generally have a deep “mental model” of what constitutes effective teaching in their fields. It is based on their personal educational experiences and is “difficult to displace, even with evidence-based alternatives.” The session will offer a brief account (with the help of a print handout) of the four “metal models” the report identifies as standing behind “good teaching”: relational, content-focused, measurable, and practical. In each, “strong feelings” shape instruction and “If advice about how to teach conflicts with these personal feelings about good teaching, faculty are likely to reject it even if it comes from scientific studies of effective instruction and improved learning.” Professors are most likely to accept technological innovation when it is “compatible with the specific tenets at the core of their instructional identities.”
While CMU has been influential in codifying principles of the learning sciences for higher education in the fully automated courses making up its famed Online Learning Initiative, it acknowledges that its own faculty displays considerable diffidence about applying them to their own teaching. As Herckis told EdSurge in an interview about the project: “For faculty who believe that teaching is an art, that it is just something that you develop with experience and time. . . . no amount of exposure to learning science research is going to disrupt their sense that this is something you learn by doing, that they need to follow their gut on.” Accordingly, efforts to make a place for the learning sciences means adapting its theoretical propositions in a demanding partnership of course designers and instructors.
With the competing positions on bringing theory to practice as a backdrop--including wariness of constructing them as an unyielding binary--participants in the session will be invited to consider what their experience tells them about the merits of each and what activities may be available to close the space between skeptical teaching identities and learning science oriented course design.
Questions like these can offer participants opportunities to express their views: “Can the different “identities” and instructional strategies reflecting the learning sciences be seen as complementary?” If so, “What can be done to identify and mobilize the ‘drive to innovate’?” “Where is the best place to begin in the integration of the learning sciences into course design?” And “How can attention to the learning sciences be coordinated with older theoretical initiatives, like Asynchronous Learning Networks and the Community of Inquiry, or the group of practices, borrowed from the face-to-face classroom, known as “Active Learning?” Conversely, to recognize the durability of the competition between different ideas about teaching and technology: “Are the ‘roadblocks’ to adopting the learning science approach too daunting to count on the technological transformation of teaching its advocates anticipate?” “Is there a case for recognizing resistance to innovation as a legitimate feature of teaching for some professors?” And, “Where do instructional designers themselves see the limits of remaking the foundations of teaching according to the learning sciences?”