Daniel L. Schwartz

Bio: Daniel L. Schwartz is an academic researcher from Stanford University. The author has contributed to research in topics: Educational technology & Learning by teaching. The author has an hindex of 46, co-authored 144 publications receiving 11868 citations. Previous affiliations of Daniel L. Schwartz include Vanderbilt University & Peabody College.

Doing with Understanding: Lessons from Research on Problem- and Project-Based Learning

Abstract: (1998). Doing With Understanding: Lessons From Research on Problem- and Project-Based Learning. Journal of the Learning Sciences: Vol. 7, No. 3-4, pp. 271-311.

A time for telling

Abstract: Suggestions for improving text understanding often prescribe activating prior knowledge, a prescription that may be problematic if students do not have the relevant prior knowledge to begin with. In this article, we describe research about a method for developing prior knowledge that prepares students to learn from a text or lecture. We propose that analyzing contrasting cases can help learners generate the differentiated knowledge structures that enable them to understand a text deeply. Noticing the distinctions between contrasting cases creates a "time for telling"; learners are prepared to be told the significance of the distinctions they have discovered. In 3 classroom studies, college students analyzed contrasting cases that consisted of simplified experimental designs and data from classic psychology experiments. They then received a lecture or text on the psychological phenomena highlighted in the experiments. Approximately 1 week later, the students predicted outcomes for a hypothetical experiment that could be interpreted in light of the concepts they had studied. Generating the distinctions between contrasting cases and then reading a text or hearing a lecture led to more accurate predictions than the control treatments of (a) reading about the distinctions between the cases and hearing alecture, (b) summarizing a relevant text and hearing a lecture, and (c) analyzing the contrasting cases twice without receiving a lecture. We argue that analyzing the contrasting cases increased students' abilities to discern specific features that differentiated classes of psychological phenomena, much as a botanist can distinguish subspecies of a given flower. This differentiated knowledge prepared the students to understand deeply an explanation of the relevant psychological principles when it was presented to them. These results can inform constructivist models of instruction as they apply to classroom activities and learning from verbal materials. In particular, the results indicate that there is a place for lectures and readings in the classroom if students have sufficiently differentiated domain knowledge to use the expository materials in a generative manner.

Chapter 3: Rethinking Transfer: A Simple Proposal With Multiple Implications

Abstract: A belief in transfer lies at the heart of our educational system. Most educators want learning activities to have positive effects that extend beyond the exact conditions of initial learning. They are hopeful that students will show evidence of transfer in a variety of situations: from one problem to another within a course, from one course to another, from one school year to the next, and from their years in school to their years in the workplace. Beliefs about transfer often accompany the claim that it is better to ' 'educate'' people broadly than simply to \"train\" them to perform particular tasks (e.g., Broudy, 1977). In this chapter, we discuss research on transfer from both a retrospective and a prospective perspective. What has past transfer research taught us that is especially important for education? What might research on transfer look like in the future? Our discussion of past research is brief, not because it is unimportant but because of space limitations and the fact that our primary emphasis is on the future. We argue that prevailing theories and methods of measuring transfer are limited in scope; we propose an alternative that complements and extends current approaches; and we sketch this alternative's implications for education. Our discussion is organized into five sections. First, we briefly summarize some of the key findings from the literature on transfer—both the successes and the disappointments. Second, we contrast the \"traditional\" view of transfer with an alternative that emphasizes the ability to learn during transfer. Third, we discuss mechanisms for transfer that emphasize Broudy's analysis of \"knowing with\" (which he adds to the more familiar replicative \"knowing that\" and applicative \"knowing how\"). Fourth, we show how our alternate view of transfer affects assumptions about what is valuable for students to learn. Finally, we show

Inventing to Prepare for Future Learning: The Hidden Efficiency of Encouraging Original Student Production in Statistics Instruction.

Abstract: Activities that promote student invention can appear inefficient, because students do not generate canonical solutions, and therefore the students may perform badly on standard assessments. Two studies on teaching descriptive statistics to 9th-grade students examined whether invention activities may prepare students to learn. Study 1 found that invention activities, when coupled with subsequent learning resources like lectures, led to strong gains in procedural skills, insight into formulas, and abilities to evaluate data from an argument. Additionally, an embedded assessment experiment crossed the factors of instructional method by type of transfer test, with 1 test including resources for learning and 1 not. A "tell-and-practice" instructional condition led to the same transfer results as an invention condition when there was no learning resource, but the invention condition did better than the tell-and-practice condition when there was a learning resource. This demonstrates the value of invention activ...

How people learn: Brain, mind, experience, and school.

Abstract: New developments in the science of learning science of learning overview mind and brain how experts differ from novices how children learn learning and transfer the learning environment curriculum, instruction and commnity effective teaching - examples in history, mathematics and science teacher learning technology to support learning conclusions from new developments in the science of learning.

Remembering. A Study in Experimental and Social Psychology, Cambridge (University Press) 1964.

Abstract: Part I. Experimental Studies: 2. Experiment in psychology 3. Experiments on perceiving III Experiments on imaging 4-8. Experiments on remembering: (a) The method of description (b) The method of repeated reproduction (c) The method of picture writing (d) The method of serial reproduction (e) The method of serial reproduction picture material 9. Perceiving, recognizing, remembering 10. A theory of remembering 11. Images and their functions 12. Meaning Part II. Remembering as a Study in Social Psychology: 13. Social psychology 14. Social psychology and the matter of recall 15. Social psychology and the manner of recall 16. Conventionalism 17. The notion of a collective unconscious 18. The basis of social recall 19. A summary and some conclusions.

스크린 위의 삶 = Life on the screen : identity in the age of the internet

Abstract: From the Publisher: A Question of Identity Life on the Screen is a fascinating and wide-ranging investigation of the impact of computers and networking on society, peoples' perceptions of themselves, and the individual's relationship to machines. Sherry Turkle, a Professor of the Sociology of Science at MIT and a licensed psychologist, uses Internet MUDs (multi-user domains, or in older gaming parlance multi-user dungeons) as a launching pad for explorations of software design, user interfaces, simulation, artificial intelligence, artificial life, agents, "bots," virtual reality, and "the on-line way of life." Turkle's discussion of postmodernism is particularly enlightening. She shows how postmodern concepts in art, architecture, and ethics are related to concrete topics much closer to home, for example AI research (Minsky's "Society of Mind") and even MUDs (exemplified by students with X-window terminals who are doing homework in one window and simultaneously playing out several different roles in the same MUD in other windows). Those of you who have (like me) been turned off by the shallow, pretentious, meaningless paintings and sculptures that litter our museums of modern art may have a different perspective after hearing what Turkle has to say. This is a psychoanalytical book, not a technical one. However, software developers and engineers will find it highly accessible because of the depth of the author's technical understanding and credibility. Unlike most other authors in this genre, Turkle does not constantly jar the technically-literate reader with blatant errors or bogus assertions about how things work. Although I personally don't have time or patience for MUDs,view most of AI as snake-oil, and abhor postmodern architecture, I thought the time spent reading this book was an extremely good investment.

The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education

Abstract: Cronbach’s alpha is a statistic commonly quoted by authors to demonstrate that tests and scales that have been constructed or adopted for research projects are fit for purpose. Cronbach’s alpha is regularly adopted in studies in science education: it was referred to in 69 different papers published in 4 leading science education journals in a single year (2015)—usually as a measure of reliability. This article explores how this statistic is used in reporting science education research and what it represents. Authors often cite alpha values with little commentary to explain why they feel this statistic is relevant and seldom interpret the result for readers beyond citing an arbitrary threshold for an acceptable value. Those authors who do offer readers qualitative descriptors interpreting alpha values adopt a diverse and seemingly arbitrary terminology. More seriously, illustrative examples from the science education literature demonstrate that alpha may be acceptable even when there are recognised problems with the scales concerned. Alpha is also sometimes inappropriately used to claim an instrument is unidimensional. It is argued that a high value of alpha offers limited evidence of the reliability of a research instrument, and that indeed a very high value may actually be undesirable when developing a test of scientific knowledge or understanding. Guidance is offered to authors reporting, and readers evaluating, studies that present Cronbach’s alpha statistic as evidence of instrument quality.