Bridging the Gap between Research and Practice: Educational Psychology- based Instructional Design for Developing Online Content Stephanie T.L. Chu Simon Fraser University Burnaby BC, Canada (see “artefacts” section)

Research Context & Purpose Context Significant research has been performed in Educational Psychology. Fields such as human-computer interaction, graphic arts and media design have had more influence in developing online materials. Instructional designers may not be aware of principles (and rationales) which stem from Educational Psychology research. A gap exists between research findings and real-life application. Purpose To aid content developers/instructors in making instructionally sound decisions when designing learning materials.

This Research… Aims to Perform a comprehensive review of the past 25 years of Educational Psychology research literature. Raise awareness about fundamental considerations. Derive a rich set of instructional design guidelines for developing learning materials. Research  ID principles  Content development. Identify categories Text presentation, examples/problems, multimedia... Include specific conditions where techniques will or will not work, identify relationships and conflicts between techniques. Note: Select findings from the past five years are covered in this paper and presentation.

Learning Cognitive Load Theory Learner Experience Instruction and Content Overview

Cognitive Load Theory

Cognitive Skills Acquisition Early Intermediate Late

Cognitive Load Theory Channels Visual/Pictorial Auditory/Verbal

Theoretical Implications Consider the mental load imposed by the learning material, learning processes, and unrelated activities. Example: Making “full use” of a computer-based medium vs. computers as a text-repository. Make use of dual-modality instruction: Present material in verbal and pictorial form concurrently. (Multimedia Principle, Moreno & Mayer, 1999) Example: Animated processes with images and text. Consider appropriate conditions. For example, avoid asking learners to: Integrate mentally corresponding representations which are separated in space or time (Split-source Instructions, Kalyuga, Ayres, Chandler & Sweller, 2003). Engage heavily in cross-referencing and search-and- match processes.

The Learner: Learner Experience Recent research investigates interactions between levels of learner knowledge (experience/expertise) in a domain and levels of instructional guidance. Additional guidance may increase or decrease cognitive load. Expertise affects whether an information source should be eliminated or not. Novices may need redundant information, but more experienced learners may experience increased extraneous load. Note: See Kalyuga, et al. (2003) for split-attention effect, redundancy effect, expertise reversal effect, elimination effect, and guidance-fading effect.

Learner Experience & Computer-based Learning Design instruction that supports the learning process and adapts instructional procedures and techniques to support individual learners. Build in prior knowledge and formative assessments (so the system can adapt). Enable some user control over multimedia such as the ability to eliminate one information source or control its pace.

Instruction and Content: Categories *Problems Problem solving, worked examples. *Multimedia Images and animation; animation and narration; pedagogical agents; “when less is more”; sequencing; Textual content Placement of main ideas and examples; text cues; text and pictures; maps

Problem Solving, Worked Examples & Problems Clearer definition of “examples” and “problems” and conditions. Relationship between worked examples/problems and learner experience and cognitive load Worked examples are effective during initial stages of cognitive skill acquisition, while in later stages, solving problems is superior. Fading out: gradual elimination of worked examples (Renkl, Atkinson, & Maier, 2000).

EarlyIntermediateLate ExperienceLittle or no domain knowledgeGaining domain knowledgeMore/high domain knowledge LearningBasic understandingStart to solve problems (understand domain & apply) Actual problem solving; optimization (understanding acquired) TaskStudy materialsUse abstract principles to solve concrete problems Practice (speed & accuracy) ApproachWorked examplesWorked examples for learners to actively self-explain/reflect. Move towards increased use of problems to solve to develop skill in this. Anticipating and imagining a previously learned solution path (introduction to problem-solving elements) for higher prior knowledge learners Problem solving (reversed worked examples effect due to redundancy effect) SkillGain basic understanding of domain Develop ability to generalize over surface structures Proceed in skill acquisition Automation of at least a subcomponent of skills (speed and accuracy) Intrinsic load The material being studiedMaterial being studied (gradual decrease in load as cognitive skill acquisition increases) Material being studied (less load) Germane load Worked examplesSelf-explanations (principle-based explanations, goal-operator relations, coherence among examples) Anticipating and imaging based on what has been learned to-date Problem-solving Extraneous load Steps in problem solving Redundant information (examples) Self-explanations Alternative(Renkl & Atkinson, 2003) N/A Fading worked-out solution steps: 1.Present concrete example (model) 2.Present example where one single solution step is omitted (coached problem solving) 3.Increase the number of blanks step-by-step until only the to-be-solved problem remains (independent problem solving) Cognitive load N/AFading reduces heavy cognitive load and reduces errors in learning. By implementing a step-by-step approach, demands gradually increase. Appropriate for N/AFor problems solvable by applying specific “to-be-learned” rules (near-transfer) where reducing errors is advantageous Fading can be used for problems that require modification of learned solution methods (far transfer). Though learned roles cannot be directly applied, errors may trigger reflection and deepen understanding of the domain. Mapping out Learning & Experience Against the Use of Examples & Problems

Problem Solving, Worked Examples & Problems Presenting content online may provide options for students as their experience levels increase System moves learners from worked examples to problems or “fade-out”. Multimedia can offer novel instructional opportunities: Learning objects can depict an expert’s thought processes. Aural and visual modeling.

Multimedia Numerous studies examine using both channels of working memory such as through animation. ( Mayer & Associates (i.e. Moreno, 1998-present) and others (e.g. Atkinson, 2002)) Key ideas: Learning materials that make use of both the visual and verbal channels of information processing (working memory) are more effective for learning than a single representation of information or multiple representations through the same modality. Example: Animation and narration rather than narration alone. Example: Animation and narration is a better combination than animation and on-screen text (both require processing by visual channel). Animation and narration should be presented concurrently rather than consecutively so that students develop a stronger sense of the association between the information seen and heard.

Multimedia Research on pedagogical agents (animated “guides”) is fairly new and requires further examination. “When less is more” More ways of presenting the same information within resources (information delivery hypothesis), is not necessarily better (cognitive load effect, redundancy effect) For optimal multimedia use, select resources that have only one verbal and visual component (avoid split-attention effect). Seductive details (“interesting” unimportant information related to the learning materials) may have neutral to negative effects. Thought to encourage interest in the topic (emotional interest hypothesis), but this is not supported. Design or select materials that do not contain extraneous words, sounds (including music), and video which can distract learners (take away from germane cognitive load).

In Conclusion General Implications Need for designers to consider cognitive processes associated with learning. The extent to which cognitive load comes into play depends on the learner (specifically, domain experience/expertise). Computer-based learning can provide novel interactive learning opportunities which capitalize on multimedia and the ability to adapt to an individual learner. Paper and presentation available: (see “artefacts” section)