Sommerhoff 2018 What Do We Teach When We Teach the Learning Sciences

Citation

Daniel Sommerhoff, Andrea Szameitat, Freydis Vogel, Olga Chernikova, Kristina Loderer and Frank Fischer. “What Do We Teach When We Teach the Learning Sciences? A Document Analysis of 75 Graduate Programs.” Journal of the Learning Sciences 27(2): 319-351. Taylor & Francis, published online Apr. 10, 2018. Open access, CC BY-NC-ND 4.0. https://doi.org/10.1080/10508406.2018.1440353. Copy: raw/shared/2026-10-28 Sommerhoff 2018 What Do We Teach When We Teach the Learning Sciences.md (original: .pdf beside it). Read 2026-10-28.

Bottom line

The authors coded the English websites of 75 graduate learning sciences programs in 2015. Computer science takes part in 48 percent of the programs, more than any other discipline.
“Using technology to support learning” is the most common concept: 76 percent of programs mention it. Design-based research (DBR) marks the most similar group of programs.
It is evidence about program websites, not about what students learn.

Background

The footnotes support its definition of the science of learning. Footnote 4 supports: “how people learn, how to support learning, how to facilitate and enhance learning, discipline-based learning, and the role of technology in enhancing learning and collaboration”. Footnote 5 (“Ibid.”) supports: “how people process, gather, and interpret information; how they develop knowledge, skills, and expertise; and the extent to which social and physical context and design environments influence learning”.

The paper supports both. On p. 322 it names “how people learn, supporting learning, learning in the disciplines, and technology-enhanced learning and collaboration”. The same page has “how children and adults process, gather, and interpret information or actions and how they develop knowledge, skills, and expertise”. It also stresses “the social and physical context of cognition”. The proposal paraphrases closely and keeps the meaning.

Key claims

Sample (p. 328): “The sample consisted of 75 graduate learning sciences programs: 38 master’s degree programs (51%) and 37 PhD programs (49%).” Of these, 43 (57 percent) were at member universities of the Network of Academic Programs in the Learning Sciences (NAPLeS).
Location (p. 332): “a high concentration in North America of all programs was found, with 71% (n = 53)”. Europe had 20 percent (n = 15), and Asia and Australia 9 percent (n = 7). No program was in South America or Africa.
Disciplines (p. 332, Table 2): 45 disciplines in total. The top five: computer science 48 percent, psychology 35 percent, science and science education 35 percent, engineering 25 percent, education 21 percent.
Concepts (p. 333): “Using technology to support learning is the most prevalent, with 76% of the programs explicitly mentioning it”. Five other concepts reach about 60 percent each. “Nonsituative instructional approaches” reach 13 percent.
Methods (p. 333): most method mentions were unspecified: data collection 39 percent, data analysis 47 percent. “DBR as well as basic statistics are each covered by more than 20% of the programs, whereas all other methods are only mentioned by less than 15% of the programs each.”
Emphasis (p. 336): technology to support learning is 27 percent of all emphasis codes. Designing learning environments and scaffolding is 17 percent, and cognition and metacognition 15 percent.
Core programs (p. 341): “those programs teaching DBR show the highest similarity (κ = .43)”. Programs that share basic statistics (κ = .21) or questionnaires (κ = .10) show the lowest similarity.
DBR share (p. 346): “merely 25% of the graduate programs that self-categorize as learning sciences programs explicitly address DBR.”
Description (p. 346): “Technology is key for supporting and scaffolding individuals and groups to engage in productive learning activities.”

Evidence and method

Design (p. 327): a document analysis of program websites, with qualitative content analysis, network analysis and a similarity measure (Fleiss’ kappa).
Search (pp. 327-328): web search engines, International Society of the Learning Sciences (ISLS) materials and the NAPLeS program list. Only programs with English websites and enough description qualified.
Data dates (p. 328): the authors compiled the list “in early 2015”. The download ran from late June 2015 to July 31, 2015.
Coding (p. 330): four coders. Agreement on 16 programs ranged “from 75% to 94% (M = 84%, SD = 7%)”. Weighted agreement ranged from 66 to 92 percent.
Peer-reviewed, in the field’s main journal, open access.

Limits

Websites are not curricula. The authors write: “websites are created at least partially for marketing purposes” (p. 345).
English websites only, and only programs that use the label “learning sciences” (p. 345).
The data is from 2015. Programs, and the role of AI in them, have changed since then.
The paper is about learning science research training. It is not about computing or AI workforce training.

Source file: wiki/sources/Sommerhoff 2018 What Do We Teach When We Teach the Learning Sciences.md, updated 2026-10-28.