Using scenarios to design complex technology-enhanced learning environments
- 3.6k Downloads
Science Created by You (SCY) learning environments are computer-based environments in which students learn about science topics in the context of addressing a socio-scientific problem. Along their way to a solution for this problem students produce many types of intermediate products or learning objects. SCY learning environments center the entire learning process around creating, sharing, discussing, and re-using these learning objects. This instructional approach requires dedicated instructional designs, which are supplied in the form of what are called pedagogical scenarios. A SCY pedagogical scenario presents the learning process as an organized assembly of elementary learning processes, each associated with a specific learning object and a tool for creating this learning object. Designing a SCY learning environment is basically a two-step procedure: the first step is to select one of the available scenarios, and the second step is to define the domain content. The SCY technical infrastructure then handles the instantiation of the scenario as a SCY computer-based learning environment. In this article we describe the SCY pedagogical design scenarios and report on our experiences in designing four different SCY learning environments.
KeywordsInstructional design Open learning environments Learning by design Inquiry learning Collaborative learning
Contemporary, constructivist-based, technology-enhanced learning environments provide students with ample opportunities for inquiry and/or collaboration. In these environments, the affordances offered by technology are used directly for pedagogical purposes. Inquiry calls for non-linear, manipulable, and runnable content, and collaboration (in particular when asynchronous or online) is enabled by different communication media and the opportunity to share content. Some examples of such environments are Belvedere (Suthers et al. 1995), BioWorld (Lajoie et al. 2001), SimQuest environments (van Joolingen & de Jong 2003), Co-Lab (van Joolingen et al. 2005), WISE (Slotta 2004), Inquiry Island (White et al. 2002), Young Scientist (Mäeots et al. 2008), Genscope (Horwitz et al. 2010), and Stochasmos (Kyza et al. 2011). Evidence is accumulating that these approaches provide students with genuinely effective learning opportunities. Large scale evaluations, conceptual overviews, and meta-analyses have shown that inquiry, if scaffolded, outperforms other forms of instruction (Alfieri et al. 2011, 2011; Deslauriers & Wieman 2011; Eysink et al. 2009; Hickey et al. 2003; Linn et al. 2006; Marusić & Slisko, 2012; Plass et al. 2012; Rutten et al. 2012; Scalise et al. 2011; Smetana & Bell, in press), and the effectiveness of collaboration compared to individual learning has also been demonstrated (see e.g., Gijlers & de Jong, 2009; Kolloffel et al. 2011; Lou, 2004; Lou et al. 2001).
A third instructional approach that is aligned with the basic constructivist principles of inquiry and collaboration is learning by design. Here, students learn by creating products; the literature suggests that this method of learning helps specifically with the acquisition of transferable knowledge (Etkina et al. 2010; Kolodner et al. 2003; Mehalik et al. 2008). Unlike the situation for inquiry and collaboration, there is little software that specifically enables learning by design. The environments coming closest to learning by design are those that support students in making computer models of phenomena (see e.g., de Jong & van Joolingen 2007; Shen & Linn 2010; Wilensky & Reisman 2006).
The Science Created by You (SCY) project creates learning environments (called SCY ‘missions’) that combine all three of these instructional approaches. A central tenet of SCY missions is that students learn by creating products (design), and that in doing so they investigate learning materials (inquiry) and share and discuss their products with peers (collaboration). The main purpose of the current article is to give an outline of the design principles underlying the creation of SCY missions, in which the use of the templates or blueprints known as pedagogical scenarios is central. We begin by giving a brief sketch of what a SCY mission looks like from the student’s perspective and an impression of student experiences, followed by the central part of the paper, the presentation of our design approach, and a report of our experiences in designing four different SCY missions.
SCY for students
SCY uses the metaphor of the student as an engineer or scientist who gathers knowledge in the course of working on a research or design project. Therefore, SCY missions are characterized by an overall research or design goal, e.g., to create a report on water quality or to create a CO2-friendly house. Along their way to this final product students create many types of (intermediate) products. An example of such a product in the CO2-friendly house mission is a set of hypotheses on the effects of measures that reduce CO2 emission. We have called these products that are created in SCY missions Emerging Learning Objects (ELOs). Examples of types of ELOs include: runnable models, concept maps, data sets, hypotheses, tables, summaries, reports, and experimental procedures.
To date, four SCY missions have been developed, each of which addresses specific science content in the context of creating a particular final product. Students in the CO 2 -friendly house mission are assigned the task of designing a CO2-friendly house. In this mission, students must describe how domestic CO2 emission occurs and how much of it occurs, and find out how it can be controlled. They take into account materials and how energy is supplied, and list the requirements and constraints for their house. Learning goals include knowledge of physics, such as knowledge of types of energy (potential, kinetic, thermal, chemical, electromagnetic) and of the first law of thermodynamics, as well as mathematical knowledge, such as knowing how the ratio of surface area to volume changes with the size and shape of a specific object. ELOs that need to be produced along the way include a concept map on CO2 emission, a set of hypotheses about the energy household of a specific house, and data sets from two different simulations (a house simulation and an energy consumption simulation). The students’ final product is a 3D-drawing of their house and an accompanying report that gives the rationale for their design choices.
The ECO mission is intended for learning about topics at the junction of biology and ecology. These topics are: (a) the influence of nutrient concentration on primary production, (b) influences of light on the level of photosynthesis, (c) relations between trophic levels in an ecosystem, and (d) the concept of pH and changes of pH in bodies of water. The selected topics enable students to encounter real-life problems (e.g., what bait to use to catch fish). Students’ final products are a concept map about relations in an ecosystem and a video report that illustrates the inquiry processes that they have applied. ELOs that need to be created during the learning process are research questions and hypotheses, experimental procedures, data sets from mobile devices measuring water quality, dynamic models, and inferences from data.
In the Healthy Pizza mission the final product that must be designed is a healthy pizza (either in the form of a real pizza or using a simulation). Topics that students address in this mission are the nutritional value of food items in general (carbohydrates, fat, proteins, energy, vitamins, etc.) and of various pizza ingredients in particular, the classification of food products (grains, fruits, vegetables, milk, meat, and beans), and information on energy (calories) and the human digestive system. ELOs that need to be created en route to the healthy pizza include a personal health passport, a nutrition table, a map of the digestive system, and a food pyramid.
In the forensic mission students are engaged in an investigation to find a criminal offender. They must identify the techniques they will use to analyze DNA or ink samples, elaborate or justify their experimental procedure, carry out real experiments, and analyze their results. Students deal with concepts about DNA (universality, structure, sequence of nucleotides), biological techniques (electrophoresis gel, restriction enzymes, DNA profiling), chemistry (solution, solvent, solubility), chemical techniques (thin layer chromatography, identification and separation techniques), and mathematics (frequency, match probability). Examples of ELOs that students need to create are a concept map on techniques for chemical analyses, texts such as a definition of DNA or the justification of chromatography as a relevant technique for analysis of ink, expected results of the experiments, experimental procedures for the chemical analysis, pictures of experimental results (e.g., taken with a mobile phone), and calculations of DNA profile frequencies in the human population. The final product is a report for the attorney general that will help to solve the case.
The CO2, ECO, and forensic missions aim for students in the 16–19 age group, while the Healthy Pizza mission is intended for a somewhat younger group of 12- to 15-year-olds. The estimated duration of a mission ranges from 16 h (ECO and Forensic missions) to 20 h (CO2 and Healthy Pizza missions). However, there is some flexibility built into the missions that makes it possible to use them even if less lesson time is available. For example, the ECO mission covers four topics that can be completed independently, in about 4 h each.
The (interface) design of SCY missions
In the interface presented in Fig. 1, taken from the ECO mission, students are composing an ELO called ‘experimental procedure’. A number of thumbnails of other ELOs that students also need to complete are visible on the screen. The four drawers to the left of the ELO contain (1) an assignment that explains what students should do; this drawer is extended in Fig. 1 (labeled ‘Assignment’), (2) resources (e.g., texts or hyperlinks) that can help in completing the ELO, (3) a feedback request option and (4) an option for adding tags to the ELO, such as tags that may help in later searches for ELOs. Communication about an ELO under edit is closely connected to the ELO itself. As can be seen in Fig. 1, a chat is directly tied to the ELO in a drawer that extends to the right from the ELO, which students can open and close. Students can also ask for comments from other students on their ELO by opening the third drawer to the left of the ELO and asking for feedback. This request is then propagated to other students.
Description of the LAS ‘Experimentation’
Define experiment goal
Choose variables (what is going to be tested?) and values (what values of variables are implemented?)
Design an experimental procedure
Operationalize the variables and specify conduct of the experiment
Apply experiment design (for simulation or field or laboratory experiment)
Convert between different representations, e.g., visualize in graphical form; aggregate data
Aggregation, choice of scales, graph, table, diagram
Make a local interpretation of data (without reference to the hypothesis)
Local interpretation of data
Compare results of different experiments
List of differences between experiment results
Scaffolding for students
Students’ experiences with SCY missions
The four SCY missions have been tested with over 600 students from five different countries. We have used a series of different techniques in evaluating students’ experiences, including analyses of video recordings, screen captures, and logfiles, as well as analysis of ELOs produced by students (see, Kluge et al. 2011). The data from evaluation of these experiences were used in an iterative design approach to create the interface of the learning environment in its current form. For example, in the course of the design process the navigation features became more structured and explicit for students; in particular, the mission map was added to present students with an overview of the mission. Overall, students had (surprisingly) little trouble navigating through a SCY mission, but to support them further we developed a brief introductory ‘mini-mission’ that introduces students to the main aspects of a SCY mission. We also developed a number of help videos that explain the main functionalities of the learning environment, and we implemented ‘bubble’ help for all of the main elements in each SCY mission. Because ELO creation and re-use is of paramount importance in the SCY learning experience, we looked at students’ ability to assess and re-use each other’s ELOs. Two case studies revealed that students appreciated and used the opportunity to inspect the work of their peers. However, results also showed that additional support is necessary for students to make productive use of peer-created ELOs. Three processes in particular appeared to be difficult for students: deciding what information to look for, selecting relevant ELOs, and judging the quality of these ELOs. A follow-up study confirmed that students who received scaffolding for these processes considered the contents of peer-created ELOs in greater depth and therefore created better ELOs of their own than did students without additional support (Kluge, et al. 2011). In another study we examined how students assessed each other’s ELOs, and concluded that students (seventh graders, in this case) could in principle give relevant peer feedback on ELOs, but that their skills still needed further development (Tsivitanidou et al. 2011). Although we have not yet compared learning with SCY missions to conventional instructional approaches, in a number of recent studies we have been able to confirm that, measured through pre- and post-tests, students who learned with a SCY mission made considerable progress in their inquiry skills as well as their domain knowledge (Kluge et al. 2012).
The student’s view of a SCY mission in summary
SCY for instructional designers
As stated in the introduction, technology-enhanced learning environments for inquiry, collaboration, and to a lesser extent, learning by designing, are not new. There is also a large set of instructional design theories that prescribe how these kinds of environments should be designed. Because of the learner centered character of the learning environments that are designed, some authors prefer to use the term “learning design” (see e.g., Sims 2006). In the remainder of the article we will, however, use the term “instructional design” to better stay in line with the mainstream literature. Some of the (classical) theories are general in character (Dick & Carey 1990; Gagné et al. 1988), while others focus on a specific learning approach, such as inquiry (e.g., Spector & Davidsen 2000). These theories have proven to be very helpful for designing learning environments, but even the more specific ones limit themselves to providing designers with general guidelines (such as: “challenge the learner to diversify and generalize”, Spector & Davidsen 2000, p. 256) that still need to be translated into an actual design. Our goal in the SCY project is to realize multiple different missions, which requires a designated and formalized instructional design method. Having such a design method means that the development of new missions with new content can benefit from re-usable design elements. This helps to decrease mission development time, and also allows different educational designers to develop missions while maintaining a consistent pedagogy. Moreover, having a formalized and unified format for describing the pedagogical design of SCY missions allows systematic comparison between different scenarios and the way they incorporate inquiry, design, and collaboration. In this way, design decisions are made overt and can be compared and debated. The instructional design method we developed in SCY is formalized in what are called ‘pedagogical scenarios’ that we have used to realize four missions so far (see the descriptions above), with additional new missions currently under development.
Scenarios, blueprints for instructional design
The design process for a SCY mission is based on the same structure as the student’s view presented in Fig. 3. To create a mission, a designer starts at the highest level of abstraction and first selects a ‘pedagogical scenario’ from a fixed collection of scenarios that was created by the SCY development team. A pedagogical scenario is always composed of a set of interconnected LASs, each LAS consists of a set of ELOs, and each ELO has an associated learning activity and a tool for creating it. In the remainder of this section we will describe these different components of the design process, starting at the lowest level, the ELO with associated activities and tools, then moving to the LASs, and finally presenting the available set of scenarios.
Our creation of the pedagogical scenarios proceeded in the opposite direction from that taken by a SCY mission designer. We started at the lowest level of abstraction by defining a set of basic learning activities, based on existing frameworks of such activities (Anderson & Kraftwohl 2001; Azevedo et al. 2004; Ferguson-Hessler & de Jong 1990; Mayer 2002). We identified a total of 53 learning activities that were relevant for our overall pedagogical approach. Examples of learning activities are: identify resources, distribute tasks, rehearse, build a model, ask a question, reflect on (individual and group) processes, relate data with hypothesis/theory, design a (physical or virtual) artifact, build a (physical or virtual) artifact, design an experimental procedure, evaluate ELO (one’s own or a peer’s), monitor the learning process, and summarize. 1 We then defined the ELO that is produced by each activity and identified a software tool that is needed to perform the activity and produce the ELO. A straightforward example of such an activity-tool-ELO triplet is the learning activity ‘build a model’, which in case of a conceptual model may result in the ELO ‘concept map’, for which the tool ‘SCYMapper’ is available.
Next, the 53 triplets of activities with their associated ELOs and tools were clustered into 13 larger conceptual units, or LASs, that all fit within our general approach of inquiry, collaboration, and learning by design. A specific triplet could be part of more than one LAS. The LASs were labeled: Orientation, Management, Information, Conceptualization, Debate, Reflection, Analysis, Designing, Building, Experimentation, Evaluation, Regulation, and Reporting. An example is given in Table 1, which presents the activities, ELOs, and tools that form the LAS ‘Experimentation’. The tools SCYED, SCYSIM, and SCYDATA that are mentioned in the table were created for the SCY project to enable students to produce the associated ELOs; they enable students to set up an experimental design, run a simulation, and perform data analyses, respectively.
The linking arrows indicate the recommended sequences through the scenario. However, while in a mission students can also follow their own sequence of activities, and may revisit a LAS when they think this to be necessary. This allows for flexibility, in that different students can follow different routes through the scenario. The scenario of the mission is shown to the students in the mission map.
A walkthrough of the ‘design challenge’ scenario as applied in the mission ‘design a CO2-friendly house’
First, the whole project is framed by explaining the mission in which the students will engage. This mission starts with a short video explaining environment-related issues, i.e., global warming and CO2 emissions, and the overall task for the students, namely to design a CO2-friendly house. The video tells about the different choices students will have to make (selecting windows, building materials, energy sources, and more). The students write down the task in their own words
Here the students try to identify the different concepts involved in the mission. For instance, what is CO2, how is it produced, what types of activities in the house can produce it? What is energy, and how are energy and CO2 related to each other? The students use SCYMapper (the SCY concept mapping tool) to link the different elements and concepts together. Students will come back to refine their conceptual models in the course of the scenario
Students design an artifact—e.g., a house—based on the conceptual model—e.g., the model of factors that influence CO2 emissions
Students actually build a real or a simulated house artifact. In this mission we use an external tool (Google SketchUp) for that
Students design and conduct experiments with the respective artifacts they have designed. A dedicated tool (SCYED; see also Fig. 1) helps students to set up correct experiments. A simulation of a house gives students the opportunity to try out different parameters from their design
Students evaluate the data collected—e.g., by comparing results with the preset criteria and norms regarding the amount of CO2 production—and refine their conceptual models
Students reflect on whether they reached the mission goals and the learning goals (shown to them in a curtain, see Fig. 6 for an example), and explain reasons for possible deviations. They discuss how (or whether) their gradual increase in understanding led them to modify the goals of the project or if other factors such as time allotted, tool limitations, and lack of appropriate information led them to reconsider their ambitions
Students create an overview of their accomplishments and prepare a presentation to the class and the teacher
In the SCY project we have defined 12 scenarios, each of which is a different assemblage of the 13 different LASs, which, in their turn, are different assemblages of the 53 triplets of ELOs, activities, and tools.
Our design approach is thus based on choosing from a set of available scenarios. This approach ensures that structures and predefined elements in the scenario are used; furthermore, after designers have selected a scenario, they immediately have an overall structure for the mission they are creating. Scenarios thus work as blueprints for the design of missions. All scenarios are available in the SCY technical infrastructure, which handles production of the software; no programming is required from the instructional designer.
The SCY design process in practice
The four SCY missions described above were all designed on the basis of different SCY scenarios. We will illustrate the design process with the example of the ECO mission. Design of the ECO mission started by defining the target group, which was a pre-university track at high school, in the age range 16–19 years old. The learning goals were based on an analysis of the K-12 curricula in Estonia, Cyprus, Norway, France, and the Netherlands. As the mission was planned for use in all of these countries, only those topics covered in all four national curricula were selected for the mission. As a result, three topics were selected in biology and one in chemistry. Mathematics was integrated with the other subjects, as was a physics topic (light) that was included in one of the biology topics.
A set of general and domain-specific goals was specified that guided the further design of the mission. The general science learning goals referred to skills such as: being able to critically analyze information from various sources; being able to formulate hypotheses that contain measurable dependent and independent variables; being able to analyze and interpret data; and being able to design a model of a phenomenon. The domain-specific goals included: being able to explain the relations between (a) the level of O2 and population size (plants and animals), (b) the level of CO2 and population size (plants and animals), (c) light and population size (plants), (d) the environmental factors and pH of water, (e) light and photosynthesis/respiration, and (f) biomass and number of organisms in different trophic levels in an ecosystem. In addition, students should learn to apply concepts in biology (e.g. abiotic and biotic factors, photosynthesis, respiration, population size, trophic levels), physics (propagation of light, temperature), and chemistry (pH) in a conceptually coherent way. Finally, they should learn to model the changes and balance in an ecosystem (level of O2, CO2, pH, light, population size, temperature) and to apply domain-specific experimental procedures (measurement of O2, CO2, pH, light, population size, temperature).
The general science learning goals made the ‘Inquiry Learning’ scenario the obvious choice. This scenario was especially designed for developing students‘inquiry skills; the learning goals defined above map onto both the overall aim of the scenario and the specific activities pursued in its individual LASs. In this scenario, students also acquire more general problem-solving skills, analytical skills, and self-regulation skills. Because we had four distinguishable topics in this mission, the mission was set up as four inquiry cycles, one for each of the four topics.
After having made the choices of a target group, learning goals, and scenario, domain content was formulated. This content was created based on the national curricula that were analyzed, a review of the relevant literature, and the domain expertise of the designers. In order to identify additional content for this mission, six domain experts (three ecologists and three science teachers) from Estonia, Cyprus, and the Netherlands were interviewed. They were provided with a list of misconceptions and knowledge gaps derived from a literature review. The experts were asked to rate the importance of the issues and to add new elements based on their own experience. The information collected from the literature review and expert interviews was used to develop mission-specific resources, which were then evaluated by a group of science teachers.
Experiences with the design of four missions
In designing, the creation of learning goals and the choice of a scenario happened close together. Because scenarios bring general science learning goals with them, designers supplemented their original learning goals quickly with learning goals that were part of the selected scenario.
Designers did not follow a scenario unthinkingly, but left out LASs they found less relevant and also excluded learning activities/ELOs within LASs that they thought did not fit into the specific mission. In this way, the scenario functioned as an overall framework from which elements could be omitted. However, the character and structure of the scenario were preserved overall.
A given scenario may direct students to return to a LAS two or even more times, typically with the objective of adapting or updating an ELO. Therefore, sometimes the choice was made to have multiple LASs of the same kind in the same SCY mission, so that students could identify the ‘phase’ of the mission in which they were working.
Several times LASs were also combined, in order to make student navigation easier.
It was also necessary divide the larger missions (ECO, Healthy Pizza, and forensic missions) into a number of content-related parts, each of which followed the scenario individually. That is, each part followed either a phase in the scenario or a complete scenario, depending on the mission.
The main change with regard to the original design process was that the initial two-step design process (select scenario, instantiate with content) was extended with an intermediate stage in which designers adapted a scenario by leaving out LASs (or within LASs leaving out specific ELOs with associated learning activities) that they did not find applicable for their specific context. In his commentary on a number of Instructional Design (ID) tools that were described in a special issue of ETR&D (vol. 50, 2), Gustafson (2002) stated that whatever ID tool is being used, it only becomes a valuable tool in the hands of a skillful designer: “The degree of both general and specific ID and subject matter expertise expected of tool users is a central factor when considering its application.” (Gustafson 2002, p. 60). The observations above underscore Gustafson’s point that instructional designers (should) mold the design process toward their own needs and desires, as is supported in the SCY approach.
Discussion: The SCY design approach in relation to other instructional design approaches
The design and development of technology-enhanced learning environments is a costly and time-consuming endeavor. Each and every aspect of a learning environment needs to be designed from both a content and an instructional perspective, and implemented in software. Estimates of the number of hours required to produce 1 h of instruction have ranged from 100 (Tannenbaum 2001) to 300 (Merrill & ID2 Research Group 1998). Therefore, it is not surprising to see that there has been a search for tools to help reduce production time and at the same time improve instructional design quality (Merrill 2002a). Reuse is one of the mechanisms that supports time efficiency and quality assurance (Murray 1999). Reuse may refer to the content of a learning environment or to the instructional design or to both. When the content and instructional design have been taken into account adequately, reuse may also refer to the technical realization of a learning environment. This means that components can be reused more or less directly in a technology-enhanced learning environment, without additional programming. In SCY we have focused on the re-use of the instructional design, in the form of re-usable scenarios that are already programmed in a learning environment. SCY scenarios can be adapted by designers, as was done in practice. Moreover, through an authoring system designers can set specific parameters in the learning environment, such as the level of scaffolding. Designers can even decide to create completely new scenarios with the use of a scenario tool that is available in SCY. In this way, we tried to combine the ease of pre-defined and re-usable structures and, for more advanced use, far-reaching facilities for adaptability. As Murray (1999) explicitly mentions, customization, extensibility, and scriptability are key characteristics of proficient authoring systems.
In SCY, the instructional design approach must be able to realize learning environments with an open and complex structure. Design for ill-structured problems, such as SCY missions, creates a set of specific challenges (Jonassen 1997). Traditionally, instructional system design (ISD) models follow a sequential (but often iterative) process that starts with defining learning goals, ends with implementation/production, and has a number of in-between phases (that may differ between different approaches) (see e.g., Merrill 2002b). The general structure of these models is often labeled as ADDIE (Analysis, Design, Development, Implementation, and Evaluation, see Rowland 1992; Visscher-Voerman & Gustafson 2004). All components of the ADDIE model are incorporated in the SCY approach, with defining learning goals in the beginning and implementation at the end, but the SCY approach has different emphases and also collapses different steps. First, based on an overall topic and idea of what students should learn, an existing pedagogical scenario is chosen rather quickly. Close together with this, the list of learning goals is also completed early in the process, partly based on what the scenario offers in the way of general science learning goals. The availability of scenarios means that parts of the design, development, and implementation phases are done together. The main, and still challenging, task for the designer then becomes to create the domain content. The SCY technical infrastructure takes care of the implementation (see de Jong et al. 2010). The evaluation phase from the ADDIE approach, finally, is realized in the SCY approach in both a formative way, because our approach enables very rapid prototyping, and also a summative way, by currently ongoing experimental and field studies.
The SCY approach to instructional design can be characterized as one of providing templates or blueprints to designers, with the idea that the designers’ task is to adapt scenarios whenever necessary and to add the right content. In this way, it follows the approach of, for example, the ADAPTIT method of supporting authors (van Merriënboer et al. 2002), but on a more detailed level. Designers receive a clear overview of all elements in a scenario and the software templates that realize them. It also resembles the SimQuest authoring approach (van Joolingen & de Jong 2003) where the overall structure was also ready-made and content needed to be included, but now with a much larger set and variety of possible scenarios.
In the SCY design approach we have tried to find a balance between providing designers with ready-made structures (scenarios) and giving them the tools and freedom to adapt these structures to their personal needs. The use of triplets of activities with ELOs and tools as the basis of our design structures allows new structures to be composed by assembling existing triplets; further, it would also be possible to create new triplets. These would then, of course, need implementation in the SCY infrastructure to allow their designs to be realized in an actual working SCY mission.
The total list of learning activities can be found at
The complete list of scenarios can be found at:
This study was conducted in the context of the Science Created by You (SCY) project, which is funded by the European Community under the Information and Communication Technologies (ICT) theme of the Seventh Framework Programme for R&D (Grant agreement 212814). This document does not represent the opinion of the European Community, and the European Community is not responsible for any use that might be made of its content. The SCY scenario repository can be found as a wiki at: http://www.scy-net.eu/Scenarios/. Our thanks go to Emily Fox (University of Maryland) and Tessa Eysink (University of Twente) for commenting on an earlier version of this article.
This article is distributed under the terms of the Creative Commons Attribution License which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited.
- Anderson, L. W., & Kraftwohl, D. R. (Eds.). (2001). A taxonomy for learning, teaching, and assessing: A revision of Bloom’s taxonomy of educational objectives. New York: Longman.Google Scholar
- de Jong, T., & van Joolingen, W. R. (2007). Model-facilitated learning. In J. M. Spector, M. D. Merrill, J. J. G. van Merriënboer, & M. P. Driscoll (Eds.), Handbook of research on educational communications and technology (3rd ed., pp. 457–468). New York: Lawrence Erlbaum.Google Scholar
- Dick, W., & Carey, L. (1990). The systematic design of instruction (3rd ed.). New York: Harper Collins College.Google Scholar
- Eysink, T. H. S., de Jong, T., Berthold, K., Kollöffel, B., Opfermann, M., & Wouters, P. (2009). Learner performance in multimedia learning arrangements: An analysis across instructional approaches. American Educational Research Journal, 46, 1107–1149. doi: 10.3102/0002831209340235.CrossRefGoogle Scholar
- Gagné, R. M., Briggs, L. J., & Wager, W. W. (1988). Principles of instructional design (3rd ed.). Fort Worth: Harcourt Brace Jovanovich.Google Scholar
- Horwitz, P., Gobert, J. D., Buckley, B. C., & O’Dwyer, L. M. (2010). Learning genetics from dragons: From computer-based manipulatives to hypermodels. In M. Jacobson & P. Reimann (Eds.), Designs for learning environments of the future: International perspectives from the learning sciences (pp. 61–89). Berlin: Springer.CrossRefGoogle Scholar
- Kluge, A., Furberg, A., Dolonen, J., Ludvigsen, S., Zacharia, Z., Xenofontos, N., et al. (2011). SCY second formative evaluation report. Deliverable DIX.3. Enschede: The SCY project. Retrieved June 8, 2012 from http://www.scy-net.eu/static/deliverables/SCY%20DIX.3.pdf.
- Kluge, A., Furberg, A., Dolonen, J., Ludvigsen, S., Strømme, T., Zacharia, Z. C., et al. (2012). SCY summative evaluation report. Oslo: Intermedia. Retrieved June 8, 2012 from http://www.scy-net.eu/static/deliverables/SCY%20DIX.4%20final.pdf.
- Kolodner, J. L., Camp, P. J., Crismond, D., Fasse, B., Gray, J., Holbrook, J., Ryan, N. (2003). Problem-based learning meets case-based reasoning in the middle-school science classroom: Putting learning by design (tm) into practice. Journal of the Learning Sciences, 12, 495–547. doi: 10.1207/S15327809JLS1204_2.Google Scholar
- Kyza, E. A., Constantinou, C. P., & Spanoudis, G. (2011). Sixth graders’ co-construction of explanations of a disturbance in an ecosystem: Exploring relationships between grouping, reflective scaffolding, and evidence based explanations. International Journal of Science Education, 33, 2489–2525. doi: 10(1080/09500693),2010,550951.CrossRefGoogle Scholar
- Mäeots, M., Pedaste, M., & Sarapuu, T. (2008, July 1–5). Transforming students’ inquiry skills with computer-based simulations. Paper presented at the 8th IEEE International Confernce on Advanced Learning Technologies, Santander, Spain.Google Scholar
- Mehalik, M. M., Doppelt, Y., & Schuun, C. D. (2008). Middle-school science through design-based learning versus scripted inquiry: Better overall science concept learning and equity gap reduction. Journal of Engineering Education, 97, 71–85.Google Scholar
- Merrill, M. D. (2002a). Instructional strategies and learning styles: Which takes precedence? In R. A. Reiser & J. V. Dempsey (Eds.), Trends and issues in instructional technology (pp. 99–106). Upper Saddle River: Prentice Hall.Google Scholar
- Murray, T. (1999). Authoring intelligent tutoring systems: Analysis of the state of the art. International Journal of AI in Education, 10, 98–129.Google Scholar
- Sims, R. (2006). Beyond instructional design: Making learning design a reality. Journal of Learning Design, 1, 1–7.Google Scholar
- Slotta, J. (2004). The web-based inquiry science environment (WISE): Scaffolding knowledge integration in the science classroom. In M. Linn, E. A. Davis, & P. Bell (Eds.), Internet environments for science education (pp. 203–233). Mahwah: Lawrence Erlbaum Associates.Google Scholar
- Smetana, L. K., & Bell, R. L. (in press). Computer simulations to support science instruction and learning: A critical review of the literature. International Journal of Science Education. doi: 10.1080/09500693.2011.605182.
- Spector, J. M., & Davidsen, P. I. (2000). Designing technology-enhanced learning environments. In B. Abbey (Ed.), Instructional and cognitive impacts of web-based education (pp. 241–261). Hershey: Idea Group Publishing.Google Scholar
- Suthers, D. D., Weiner, A., Connelly, J., & Paolucci, M. (1995). Belvedere: Engaging students in critical discussion of science and public policy issues. Paper presented at the AI&Ed 95, the 7th World Conference on Artificial Intelligence in Education, Washington, DC.Google Scholar
- Tannenbaum, R. S. (2001). Learner interactivity and production complexity in computer-based instructional materials. Retrieved June 8, 2012 from http://ubiquity.acm.org/article.cfm?id=367871.
- van Joolingen, W. R., & de Jong, T. (2003). Simquest: Authoring educational simulations. In T. Murray, S. Blessing, & S. Ainsworth (Eds.), Authoring tools for advanced technology educational software: Toward cost-effective production of adaptive, interactive, and intelligent educational software (pp. 1–31). Dordrecht: Kluwer Academic.Google Scholar
- van Joolingen, W. R., de Jong, T., Lazonder, A. W., Savelsbergh, E., & Manlove, S. (2005). Co-lab: Research and development of an on-line learning environment for collaborative scientific discovery learning. Computers in Human Behavior, 21, 671–688. doi: 10.1016/j.chb.2004.10.039.CrossRefGoogle Scholar
- Vold, V., Wasson, B., & de Jong, T. (2012). Assessing emerging learning objects: Eportfolios and peer assessment. In K. Littleton, E. Scanlon, & M. Sharples (Eds.), Orchestrating inquiry learning: Contemporary perspectives on supporting scientific inquiry learning (pp. 175–192). London: Routledge.Google Scholar
- Weinbrenner, S., Engler, J., & Hoppe, H. U. (2011). Ontology-supported scaffolding of concept maps. Paper presented at the 15th International Conference on Artificial Intelligence in Education, Auckland, New Zealand.Google Scholar
- White, B. Y., Frederiksen, J., Frederiksen, T., Eslinger, E., Loper, S., & Collins, A. (2002, October 23–26). Inquiry island: Affordances of a multi-agent environment for scientific inquiry and reflective learning. Paper presented at the Fifth International Conference of the Learning Sciences (ICLS), Seattle, WA.Google Scholar