From Seminar to Lecture to MOOC: Scripting and Orchestration at Scale

This dissertation investigates the design of large online courses from the pedagogical perspective of knowledge communities. Much of the learning sciences literature has concerned itself with groups of up to 20-30 students, but in universities, courses of several hundred to more than a thousand students are common. At the same time, new models for life-long and informal learning, such as Massive Open Online Courses, are emerging. Amidst this growing enthusiasm for innovation around technology and design in teaching, there is a need for theoretically grounded innovations and rigorous research around practical models that support new approaches to learning. One recent model, known as Knowledge Community and Inquiry (KCI), engages students in the co-construction of a community knowledge base, with a commonly held understanding of the collective nature of their learning, and then provides a sequence of scaffolded inquiry activities where students make use of the knowledge base as a resource. Inspired by this approach to designing courses, the research began with a redesign of an in-service teacher education course, which increased in size from 25 to 75 students. This redesign was carefully analyzed, and design principles extracted. The second step was the design of a Massive Open Online Course for several thousand in-service teachers on technology and inquiry, in collaboration with an affiliated secondary school. A number of innovative design ideas were necessary to accommodate the large number of users, the much larger diversity in terms of background, interest, and engagement among MOOC learners, and the opportunities provided by the platform. The resulting design encompasses a 6- week long curriculum script, and a number of overlapping micro-scripts supported by a custom- written platform that integrated with the EdX platform in a seamless manner. This thesis presents the course structure, including connection to disciplinary principles, its affordances for community and collaboration and its support of individual differentiated learning and collective epistemology. It offers design principles for scripting and orchestrating collective inquiry designs for MOOCS and higher education courses.

Mapping biological ideas: Concept maps as knowledge integration tools for evolution education

Beat Adrian Schwendimann

Many students leave school with a fragmented understanding of biology that does not allow them to connect their ideas to their everyday lives (Wandersee, 1989; Mintzes, Wandersee, & Novak, 1998; Mintzes, Wandersee, & Novak, 2000a). Understanding evolution ideas is seen as central to building an integrated knowledge of biology (Blackwell, Powell, & Dukes, 2003; Thagard & Findlay, 2010). However, the theory of evolution has been found difficult to understand as it incorporates a wide range of ideas from different areas (Bahar et al., 1999; Tsui & Treagust, 2003) and multiple interacting levels (Wilensky & Resnick, 1999; Duncan & Reiser, 2007; Hmelo-Silver et al., 2007). Research suggests that learners can hold a rich repertoire of co-existing alternative ideas of evolution (for example, Bishop & Anderson, 1990; Demastes, Good, & Peebles, 1996; Evans, 2008), especially of human evolution (for example, Nelson, 1986; Sinatra et al., 2003; Poling & Evans, 2004). Evolution ideas are difficult to understand because they often contradict existing alternative ideas (Mayr, 1982; Wolpert, 1994; Evans, 2008). Research suggests that understanding human evolution is a key to evolution education (for example, Blackwell et al., 2003; Besterman & Baggott la Velle, 2007). This dissertation research investigates how different concept mapping forms embedded in a collaborative technology-enhanced learning environment can support students’ integration of evolution ideas using case studies of human evolution. Knowledge Integration (KI) (Linn et al., 2000; Linn et al., 2004) is used as the operational framework to explore concept maps as knowledge integration tools to elicit, add, critically distinguish, group, connect, and sort out alternative evolution ideas. Concept maps are a form of node-link diagram for organizing and representing connections between ideas as a semantic network (Novak & Gowin, 1984). This dissertation research describes the iterative development of a novel biology-specific form of concept map, called Knowledge Integration Map (KIM), which aims to help learners connect ideas across levels (for example, genotype and phenotype levels) towards an integrated understanding of evolution. Using a design-based research approach (Brown, 1992; Cobb et al., 2003), three iterative studies were implemented in ethnically and economically diverse public high schools classrooms using the web-based inquiry science environment (WISE) (Linn et al., 2003; Linn et al., 2004). Study 1 investigates concept maps as generative assessment tools. Study 1A compares the concept map generation and critique process of biology novices and experts. Findings suggest that concept maps are sensitive to different levels of knowledge integration but require scaffolding and revision. Study 1B investigates the implementation of concept maps as summative assessment tools in a WISE evolution module. Results indicate that concept maps can reveal connections between students’ alternative ideas of evolution. Study 2 introduces KIMs as embedded collaborative learning tools. After generating KIMs, student dyads revise KIMs through two different critique activities (comparison against an expert or peer generated KIM). Findings indicate that different critique activities can promote the use of different criteria for critique. Results suggest that the combination of generating and critiquing KIMs can support integrating evolution ideas but can be time-consuming. As time in biology classrooms is limited, study 3 distinguishes the learning effects from either generating or critiquing KIMs as more time efficient embedded learning tools. Findings suggest that critiquing KIMs can be more time efficient than generating KIMs. Using KIMs that include common alternative ideas for critique activities can create genuine opportunities for students to critically reflect on new and existing ideas. Critiquing KIMs can encourage knowledge integration by fostering self-monitoring of students’ learning progress, identifying knowledge gaps, and distinguishing alternative evolution ideas. This dissertation research demonstrates that science instruction of complex topics, such as human evolution, can succeed through a combination of scaffolded inquiry activities using dynamic visualizations, explanation activities, and collaborative KIM activities. This research contributes to educational research and practice by describing ways to make KIMs effective and time efficient learning tools for evolution education. Supporting students’ building of a more coherent understanding of core ideas of biology can foster their life-long interest and learning of science.

University of California, Berkeley2011

The sources of process innovation in user firms

Marcellus Bogers

Previous research has shown that innovation can have various sources and different forms. Innovation can thus be developed by different types of organizations or individuals for several reasons, and it can be related to product or process technologies. One particular stream of research has explored the role of users as a source of innovation. Examples of user innovations can be found in a variety of fields and settings such as mountain biking, snowboarding, open source software, scientific instruments, oil refining, semiconductor manufacturing, and even the World Wide Web. What these innovations have in common is that they were all initially developed by people or organizations that wanted to solve a specific need and benefited from using their innovation rather than selling it. A particular type of user innovator is a "user firm" which develops new or improved production technology for its own internal use. Such process innovation is characterized by determinants and outcomes, which are fundamentally different from for example product innovation. In particular, process innovation may be driven by learning-by-doing, which is a form of problem-solving or experimentation that takes place on the production floor rather than in research and development (R&D). However, the exact drivers and consequences of process innovation in general and learning-by-doing in particular are not yet fully explored. Therefore, the objective of this thesis is to increase the understanding of the antecedents and impact of process innovation in user firms by exploring the role of non-R&D activities and learning-by-doing. This thesis consists of four parts. Each of them addresses a specific aspect related to the sources of process innovation in user firms. The first paper particularly argues that process innovation relies on different learning mechanisms than product innovation. Using data from the Swiss Innovation Survey of the Swiss Institute of Business Cycle Research (KOF) at ETH Zürich, the paper shows which are the external and internal knowledge sources (related to R&D, manufacturing and marketing) that lead to innovation. The second paper further investigates R&D and non-R&D activities as sources of innovation and develops two measures to quantify the magnitude of non-R&D innovation. The results show that a substantial part of the firms develop innovations without R&D and that non-R&D process innovation has a very large impact on the overall cost reductions in the Swiss economy. In order to better understand the sources and attributes of process innovation in user firms, a questionnaire was conducted in a sample of Swiss manufacturing firms. Based on the results, the third paper shows the pervasiveness of major and especially minor process innovation. It also explores the sources of process innovation within the firms and identifies the practices related to the accounting, protection, appropriation, and monitoring of process innovation, which are often of an informal nature. The fourth paper investigates in more detail how such practices drive learning-by-doing and process innovation. The findings firstly show which complementary systems of practices are implemented in user firms to promote the innovative contribution of production floor workers and secondly how these practices drive learning-by-doing for either major or minor process innovation.

EPFL2009

Innovation and learning performance implications of free revealing and knowledge brokering in competing communities: insights from the Netflix Prize challenge

Christopher Tucci, Juan Andrei Villarroel Fernandez

Firms increasingly use open competitions to extend their innovation process and access new diverse knowledge. The Netflix Prize case we study in this paper is a multi-stage repeat-submission open competition involving the creation of new knowledge from across knowledge domains, a process which benefits from knowledge sharing across competing communities. The extant literature says little about the effects of different types and levels of knowledge sharing behavior on the learning and innovation outcomes of such a competitive system, or what the performance boundaries may be for the system as a result of such differences. Our research explores those boundaries unveiling important tradeoffs involving free revealing behavior-defined as voluntarily giving away codified knowledge and making it into a 'public good'aEuro"and knowledge brokering behavior-defined as using knowledge from one domain to innovate in another-on the learning performance of competing communities. The results, analyzing the system-level average and volatility of learning outcomes, lead to three conclusions: (i) greater knowledge sharing, as portrayed by greater free revealing and knowledge brokering, helps achieve better average learning for the system as a whole, however, (ii) achieving the best overall outcome possible from the system actually requires controlling the amount of knowledge brokering activity in the system. The results further suggest that (iii) it should not be possible to simultaneously achieve both the best overall outcome from the system and the best average learning for the system. The tradeoffs that ensue from these findings have important implications for innovation policy and management. This research contributes to practice by showing how it is possible to achieve different learning performance outcomes by managing the types and levels of knowledge sharing in open competitive systems.

Springer2013