About

Daniel Rees Lewis is a Research Assistant Professor in the Learning Sciences at Northwestern University, affiliated with the School of Education and Social Policy. He holds a PhD and MA in Learning Sciences from Northwestern University. His research focuses on the learning sciences, contributing to the understanding of how people learn and how educational environments can be optimized to support effective learning. Lewis is involved in interdisciplinary research, teaching, and outreach within the field of learning sciences, and he is part of a community dedicated to advancing educational practices through research and collaboration.

Research topics

• Computer Science
• Psychology
• Knowledge management
• Software engineering
• Engineering
• Social psychology
• Psychotherapist
• Pedagogy
• Operations management
• Management science
• Medicine
• Process management
• Medical education
• Business
• World Wide Web
• Engineering management
• Algorithm

Selected publications

• Employing user-centered design and education sciences to inform training of diabetes survival skills

  Journal of Clinical & Translational Endocrinology · 2024-08-07 · 2 citations

  articleOpen access

  Background: Patients newly diagnosed with diabetes mellitus (diabetes), who require insulin must acquire diabetes "survival" skills prior to discharge home. COVID-19 revealed considerable limitations of traditional in-person, time-intensive delivery of diabetes education and survival skills training (diabetes survival skills training). Furthermore, diabetes survival skills training has not been designed to meet the specific learning needs of patients with diabetes and their caregivers, particularly if delivered by telehealth. The objective of the study was to identify and understand the needs of users (patients newly prescribed insulin and their caregivers) to inform the design of a diabetes survival skills training, specifically for telehealth delivery, through the application of user-centered design and adult learning and education principles. Methods: Users included patients newly prescribed insulin, their caregivers, and laypersons without diabetes. In semi-structured interviews, users were asked about experienced or perceived challenges in learning diabetes survival skills. Interviews were audio-recorded and transcribed. Investigators performed iterative rounds of coding of interview transcripts utilizing a constant comparative method to identify themes describing the dominant challenges users experienced. Themes were then mapped to adult learning and education principles to identify novel educational design solutions that can be applied to telehealth-based learning. Results: We interviewed 18 users: patients (N = 6, 33 %), caregivers (N = 4, 22 %), and laypersons (N = 8, 44 %). Users consistently described challenges in understanding diabetes survival skills while hospitalized; in preparing needed supplies to execute diabetes survival skills; and in executing diabetes survival skills at home. The challenges mapped to three educational strategies: (1) spiral learning; (2) repetitive goal directed practice and feedback, which have the potential to translate into design solutions supporting remote/virtual learning; and (3) form fits function organizer, which supports safe organization and use of supplies to execute diabetes survival skills independently. Conclusion: Learning complex tasks, such as diabetes survival skills, requires time, repetition, and continued support. The combination of a user-centered design approach to uncover learning needs as well as identification of relevant adult learning and education principles could inform the design of more user-centered, feasible, effective, and sustainable diabetes survival skills training for telehealth delivery.

  PublisherDOI

• Research Slices

  EDeR Educational Design Research · 2024-02-26

  articleOpen access1st authorCorresponding

  Educational Design Research (EDeR) methodologists argue that iteration is a core component of EDeR. Iteration is currently defined as a process of gathering more information through actions, such as testing, and using that information to improve the design. In this paper, we seek to tighten the definition of iteration to help EDeR teams conduct iterations more effectively. We argue that EDeR teams should organize their research in slices that deliver small but real value to end users while informing the design research. EDeR should pick slices that are: (a) minimal and focused, (b) deployed in a real context, (c) valuable to the end users, and (d) informative to the research. Slicing helps EDeR teams increase ecological validity when they test because it allows testing which is within real-world educational contexts or with the stakeholders who will use and be impacted by the design. Increasing ecological validity of testing is particularly important because EDeR projects tackle highly complex real-world problems with many unknown elements and relational complexity—this means it is challenging to predict what designs will have the desired impact without real-world deployment. Effective iteration through organizing research in slices helps EDeR teams to better support stakeholder goals, develop more impactful theory, and have greater and earlier impact upon education.

  PublisherOA PDFDOI

• Intelligent Coaching Systems: Understanding One-to-many Coaching for Ill-defined Problem Solving

  Proceedings of the ACM on Human-Computer Interaction · 2023-04-14 · 8 citations

  article

  One-to-many coaching is a common, yet difficult, coaching technique used in environments with many novices learning to solve ill-defined problems. Intelligent systems might be designed to support 1-to-many coaching but designing such systems requires a 1-to-many coaching model that details novices' challenges, coaches' strategies, and coaches' goals. To build such a model, we conducted interaction analysis on 24 1-to-many coaching sessions with novices developing new products in a university incubator and conducted retrospective analyses with 3 coaches and 30 novices. We contribute a model that demonstrates that coaches in a 1-to-many setting not only need to help novices develop metacognitive skills (just as in 1-to-1 coaching), but also need to utilize the presence and expertise of a group of novices to learn from each other, to mitigate their fear of failures, and provide them accountability. Our model informs design implications for future intelligent coaching systems to (1) assist coaches in monitoring and comparing many novices' progress, learning, and expertise; (2) provide novices with checklists, templates, and scaffolds to help them self-evaluate, seek-help, and summarize learning; (3) showcase failures and growth; and (4) publicize planning and progress to provide accountability.

  PublisherDOI

• Encouraging engineering design teams to engage in expert iterative practices with tools to support coaching in problem‐based learning

  Journal of Engineering Education · 2023 · 11 citations

  1st authorCorresponding
  • Computer Science
  • Computer Science
  • Knowledge management

  Abstract Background To create design solutions experienced engineering designers engage in expert iterative practice. Researchers find that students struggle to learn this critical engineering design practice, particularly when tackling real‐world engineering design problems. Purpose/Hypothesis To improve our ability to teach iteration, this study contributes (i) a new teaching approach to improve student teams' expert iterative practices, and (ii) provides support to existing frameworks—chiefly the Design Risk Framework—that predict the key metacognitive processes we should support to help students to engage in expert iterative practices in real‐world engineering design. Design/Method In a 3‐year design‐based research study, we developed a novel approach to teaching students to take on real‐world engineering design projects with real clients, users, and contexts to engage in expert iterative practices. Results Study 1 confirms that student teams struggle to engage in expert iterative practices, even when supported by problem‐based learning (PBL) coaching. Study 2 tests our novel approach, Planning‐to‐Iterate, which uses (i) templates, (ii) guiding questions to help students to define problem and solution elements, and (iii) risk checklists to help student teams to identify risks. We found that student teams using Planning‐to‐Iterate engaged in more expert iterative practices while receiving less PBL coaching. Conclusions This work empirically tests a design argument—a theory for a novel teaching approach—that augments PBL coaching and helps students to identify risks and engage in expert iterative practices in engineering design projects.

  PublisherDOI

• The Premises of Design Research

  2022-06-14 · 4 citations

  book-chapterSenior author

  Learning Sciences researchers can radically enhance the rigor, communication, and training of design research by better defining the method. We define design research as: a method conducted by researchers to create practical solutions and theoretical design models through a design process of focusing, understanding, defining, conceiving, building, testing, and presenting that incorporates other research methods, iteratively increasing rigor, to search for solutions to practical problems of human learning. This definition has six important premises. First, design research is the preferred method for simultaneously producing new practical solutions and theories. Second, design research models build upon other theoretical products. Third, DR theory consists of design models that explain the learning mechanisms underpinning practical solutions. Fourth, design research achieves its validity by incorporating methodologies across fields into the design research process. Fifth, design research achieves efficiency by using quick, low-cost methods to search broadly, followed by more rigorous empirical methods and higher fidelity implementation after identifying promising solutions and models. Sixth, scaling requires different products, not phases, of design research. Conducting design research in this way allows researchers to design theory-based solutions that are more impactful and create theories that are useful in practice.

  PublisherDOI

• Coaching Strategies to Support Teacher Iterative Practices When Redesigning Lessons (Poster 1)

  Proceedings of the 2022 AERA Annual Meeting · 2022-01-01

  article1st authorCorresponding
  PublisherDOI

• Employing User-Centered Design and Learning Science Theory to Enhance Remote Delivery of Diabetes Education and Survival Skills at Hospital Discharge

  Journal of the Endocrine Society · 2021-05-01 · 2 citations

  articleOpen access

  Abstract Learning diabetes mellitus (DM) survival skills is critically important, especially for those newly diagnosed upon discharge. COVID-19 has created new educational challenges, as DM self-management education and support is difficult to deliver remotely and can be time intensive. Content and format have not been re-designed for remote delivery; however, learning sciences research can help us create effective remote education strategies. We conducted interviews with users to identify critical needs in assuming immediate DM self-care at discharge from the hospital. We then mapped these user needs to relevant learning science theories to inform potential re-designs for remote delivery of DM education and survival skills at discharge. We conducted 12 semi-structured interviews with “users,” which included 18 participants (8 minority; 6>65 years): patients newly diagnosed with DM at discharge (N=6 [33%]), their caregivers (N=4 [22%]), and laypersons new to DM (N=8 [45%]). Users were asked about their discharge needs, laypersons about perceived needs. Three investigators performed iterative rounds of inductive coding of the transcripts (using MAXQDA software), utilizing a constant comparative method to identify codes describing dominant user needs. Learning science theory was applied to identify potential re-designs for remote delivery. Dominant user needs during hospitalization included being overwhelmed with DM self-care information (6/12 sessions) and difficulty organizing self-care equipment (5/12 sessions). Dominant user needs at home included remembering DM self-care steps (6/12 sessions), understanding correct insulin dosing (9/12 sessions), feeling fearful injecting insulin (9/12 sessions), with some noting difficulty in tracking glucose (4/12 sessions) and confusing insulin types (4/12 sessions). When learning science theory was applied, analysis mapped to three discrete educational strategies, most dominant of which is the spiral design approach—cycles of teaching the same topic but with increasing complexity. This design follows the pre-teaching principle—curriculum-based conceptual overview of self-care. Self-care at home mapped to the need for segmented learning and goal directed practice and feedback, with the potential need for behavioral therapies to reduce fear. Learning sciences has demonstrated that learning complex procedures and concepts, such as DM self-care, requires time, repetition, and continued support. With short hospital stays and the complexity of learning DM self-care, patients cannot gain needed knowledge structures to organize the information received during hospitalization. This study suggests specific learning science strategies for the design of an effective remote delivery of DM education and skills.

  PublisherOA PDFDOI

• An Emergent Understanding of Mentor Strategies for Career Development in Emerging Fields

  2021 · 6 citations

  • Computer Science
  • Knowledge management
  • Psychology

  Mentoring is a key part of career development, especially in emerging fields such as social entrepreneurship. Internet technologies have made it easier for novice social entrepreneurs to identify and connect with mentors online. Yet, we do not know the strategies mentors use to advise professionals navigating emerging fields. Knowing these strategies would allow us to create technologies for more effective career mentoring. This paper presents an expert model of career mentoring for novice social entrepreneurs. To build the model, we conducted a retrospective cognitive task analysis with 9 mentors who have at least 5 years of experience advising novice social entrepreneurs. We found that mentors help novice social entrepreneurs regulate career-related stress and make decisions about next career steps. Our findings suggest that further exploration of career mentoring strategies might allow designers to develop technologies based on the expert model, such as intelligent agents, to support and scale mentorship in emerging fields.

  PublisherOA PDFDOI

• Communicating design-based research: A workshop for creating and interpreting design arguments

  2020-01-01

  article
  Publisher

• The Logic of Effective Iteration in Design-Based Research.

  ICLS · 2020 · 10 citations

  1st authorCorresponding
  • Computer Science
  • Computer Science
  • Algorithm
  Publisher

Frequent coauthors

• Matthew W. Easterday

  32 shared

• Elizabeth M. Gerber

  29 shared

• Dr Lew s

  University of Wales

  12 shared

• Spencer E. Carlson

  Northwestern University

  7 shared

• Christopher K. Riesbeck

  6 shared

• Gustavo Umbelino

  Northwestern University

  4 shared

• Leesha V. Maliakal

  Northwestern University

  3 shared

• Emily Harburg

  3 shared