A frequently asked question at The Forensic Practice is: which adult learning principles do you incorporate in your workshops?
We know that adults are self-directed and motivated, learning best when training is relevant to their work, builds on their existing knowledge base, encourages active participation, and the methodology is clearly explained. Our instructional design is based on this understanding. Our team draws on established adult learning principles to deliver effective, engaging training that meets the needs of professionals in challenging fields. Here are some of the key principles we apply.
Science of Adult Learning
We base our workshop development and delivery on adult learning science (e.g., Brown, Roediger, & McDaniel, 2014; Khalil & Elkhider, 2016; Salas et al., 2012) and forensic interviewing research (e.g., Benson & Powell, 2015; Cordisco Steele & National Children’s Advocacy Center, 2018; Lamb, 2015; 2016; Newlin et al., 2015; Poole, 2016; Powell & Barnett, 2015; Rischke, Roberts, & Price, 2011).
Research shows that for learning to be effective and lasting:
a) training must be engaging,
b) knowledge must be deeply encoded in long-term memory,
c) skills need demonstration and correction, and
d) interviewers must maintain and practice skills over time to avoid drift.
When this does not occur, the ROI on limited training budgets is poor.
To prevent drift, we educate learners on this research. We highlight diverse contexts for applying new skills, including interviewing different age groups and conducting preliminary, comprehensive, and supplemental interviews.
We show them how they can use the activities from training to further develop and maintain their skills in the field (e.g., self-reflection, peer review). We encourage them to set individual learning goals, and provide memory aids and learning guides for use in the field (e.g., StepWise 360 Checklist).
We also offer other services to support workers in the field, including mentorship, case consultation, peer review, and advanced training.
Engagement
We foster a respectful, curiosity-driven environment grounded in social-emotional learning principles. This encourages questions and skills practice without fear of judgment.
Since engagement is critical to learning, we have dynamic trainers who motivate participants to pay attention, participate, and learn. We limit class size and use multimedia resources. We use realistic scenarios that link training to field work. We use a variety of experiential activities— incorporating gamification, improv-based games, daily feedback, and so on—to focus participants’ attention on the key aspects of each exercise.
Long-Term Memory
To support knowledge transfer to long-term memory, we apply:
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- Information processing science: learning occurs as information moves from sensory memory to short-term memory (STM) and into long-term memory (LTM).
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- Cognitive load theory: learning happens through a limited STM and an unlimited LTM.
- Cognitive load theory: learning happens through a limited STM and an unlimited LTM.
Effective learning requires managing attention, processing information within working memory limits, and strengthening long-term retention when designing curricula.
To combat fatigue and maintain engagement, we deliver knowledge in short, scaffolded segments paired with practice. We include breaks, movement exercises, offline tasks, and shorter online sessions to prevent Zoom fatigue. We manage cognitive load by ensuring learners can adequately navigate Zoom, have well-organized handouts, are given clear verbal and written instructions, and by using multimedia to share the cognitive load between the verbal and visual information channels of working memory (dual-channel principle).
We incorporate retrieval activities to deepen understanding and link new information with memory cues for easier recall. These include pop quizzes, peer teaching, brain dumps, and reflections to connect learning with applications in the field.
Specific Techniques
We intentionally include exercises that support different types of learning.
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- Experiential Learning. Activities are designed to develop insights and skills through practice and reflection (e.g., generating hypotheses exercise; note taking exercises).
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- Generative Learning. Participants solve problems before receiving solutions, with mistakes corrected as needed (e.g., interview participants exercise). This approach fosters engagement and deep learning.
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- Scaffolding. We use scaffolding principles for skills acquisition By gradually increasing the complexity of exercises and reducing trainer support, participants gain confidence and skills. We create realistic practice exercises that resemble what learners do in their work, in line with the doctrine, ‘practice like you play and you will play like you practice.’
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- Interleaved Practice. Two or more concepts or skills are practiced at once to create longer and more versatile learning.
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- Learning via Analogies. We use simple, neutral topics to help learners identify misconceptions and develop deeper insights before introducing more complex topics that apply to work contexts.
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- Scenario-Based and Problem-Solving Learning. By using fact-based scenarios (e.g., case studies, practice interviews), participants learn how to solve real-world problems in a benign training environment. This makes the material relevant and engaging, which promotes deep learning and a more flexible transfer of skills across different contexts.
- Spaced Retrieval Practice. Participants recall newly acquired material after some time delay. This makes learning more effortful and, consequently, more effective.
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- Transformational Learning. We challenge learners’ preconceived notions to make the material more meaningful. For example, they get to experience being interviewed. Consequently, they see first-hand how interviewees can become motivated to fill in the blanks and answer questions, even when they are unsure of the answer.
Strength-Based, Behavioural Feedback
We provide strength-based feedback by reinforcing effective actions, correcting mistakes, and explaining alternative approaches. This supports deep learning. Because feedback is a necessary element of skill building, we limit our class sizes to ensure that each learner receives individual attention from our trainers.
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