Instructional design is a dynamic and multifaceted endeavor filled with moments of inspiration, challenge, and growth. It’s a journey with functional milestones I have previously likened to balancing a stack of stones. The instructional design process brings a collection of instructional goals and institutional needs into balance. In this reflective narrative, I examine the experience of creating Davinci Resolve 18 training materials for University faculty with a team of fellow learning designers. Did we balance the organizational goals and the learner’s needs? Did we do so efficiently? Ultimately, did we empower through training and education?
Central to the effectiveness of instructional materials is their alignment with the target learners' unique needs, preferences, and capabilities. Reflecting on our instructional materials, we understood and focused on the intricacies of our learners' demographics, learning styles, and proficiency levels. Through rigorous analysis and feedback mechanisms, we endeavored to tailor our materials to address the diverse needs of our audience. While our efforts were commendable, there were instances where assumptions overshadowed empirical insights, potentially leading to misalignment. One particular assumption in the process was the motivational state of the audience. We assumed sufficient faculty interest in learning to produce introductory videos for their courses.
Faculty motivation to produce videos for their courses is vital for the success of online learning initiatives. Park (2011) highlights the significance of motivation theories in instructional design, emphasizing their role in understanding and fostering motivation among educators. According to Park, motivation theories provide valuable insights into the factors influencing faculty engagement and commitment to instructional tasks.
In video production, faculty motivation plays a central role in determining instructional materials' quality, quantity, and effectiveness. Motivated faculty members are likelier to invest time, effort, and creativity into developing engaging and impactful videos that enhance student learning experiences. Conversely, low motivation levels may result in subpar video content, reduced enthusiasm, and disengagement from the instructional process.
Motivation theories such as self-determination theory (SDT) and expectancy-value theory offer frameworks for understanding faculty motivation in video production. SDT posits that innate psychological needs for autonomy, competence, and relatedness drive individuals. Faculty members who feel empowered to create videos aligned with their expertise, interests, and teaching styles are more likely to be intrinsically motivated to produce high-quality content. On the other hand, expectancy-value theory suggests that motivation is influenced by the perceived value of a task and the expectancy of success. Providing faculty with resources, support, and recognition for their efforts in video production can enhance their perceived value of the task and increase their motivation to engage in this instructional practice.
Our team received a learner analysis that assumed faculty motivation. Was faculty interest in the topic adequately assessed?
Guided by the parameters outlined in the Design Case, we embarked on our quest to create and realize our instructional objectives. We took a divide-and-conquer approach to the overall body of training, delegating areas of responsibility to each learning designer. We engaged in collaborative brainstorming and iterative design processes, mutually reviewing each other's work as we progressed through the process. In retrospect, I recognize the importance of adaptability and regular checkpoints to ensure fidelity to our overarching objectives and to keep productivity on track.
If the terminus of instructional design resembles a balanced stack of stones, then that balance depends on rigorous evaluation, refinement, and evolution. One aspect emerges as a beacon for enhancement – feedback integration. While we implemented mechanisms for soliciting learner feedback, I perceive opportunities to streamline these processes for a more comprehensive yield of insights. Constructive feedback serves as the linchpin for iterative improvement, yet there were instances where our feedback loops were subject to learner bias in survey responses. I advocate for robust feedback mechanisms based on objective data collected passively in the background. This data would include time in content and the details of the interaction between the learner and the content. This type of objective data and survey responses support a culture of continuous improvement and refinement in our instructional endeavors.
The Tell, Show, Do approach in instructional design offers a structured and effective method for facilitating learning. This model emphasizes clear communication (Tell), visual demonstration (Show), and hands-on practice (Do), catering to diverse learning preferences and styles. This approach fosters a deeper understanding and retention by sequentially guiding learners through each phase, from receiving information to applying it in real-world contexts. This model’s adaptability and versatility make it valuable in the instructional designer's toolkit.
While screen captures serve as valuable visual aids in instructional materials, the duplication of effort in creating them for each procedure, alongside video demonstrations, can be inefficient. This redundancy consumes additional time and resources and risks overwhelming learners with extraneous information. Moving forward, a more streamlined approach that prioritizes the most effective instructional modalities while minimizing redundancy is warranted.
Bloom's Taxonomy, while a foundational framework in instructional design, can sometimes impose a rigid structure on writing instructional objectives. This rigidity may constrain creativity and flexibility in crafting objectives that align with the intended learning outcomes. Furthermore, questions arise regarding the relevance of Bloom's Taxonomy in today's instructional landscape. Mager's model for writing objectives offers an alternative approach, focusing on the clarity and specificity of objectives. Mager's model identifies three key components: the desired behavior, the conditions under which the behavior will be demonstrated, and the criteria for evaluating the behavior (Mager, 1997). This approach provides a more flexible and practical framework for crafting instructional objectives that effectively guide learning.
In the digital age, fostering collaborative learning environments and communities of inquiry is paramount for enriching the instructional experience. Collaborative features, such as discussion forums, group projects, and peer feedback mechanisms, facilitate active engagement, critical thinking, and knowledge sharing among learners. As described by Garrison, Anderson, and Archer (2000), communities of inquiry foster a sense of belonging and collective exploration, enhancing learning outcomes and fostering a vibrant learning ecosystem. Integrating such features into instructional materials can cultivate a culture of collaboration and inquiry, propelling learners toward deeper understanding and mastery. Our approach to Davinci Resolve 18 training needs collaborative features that support communities of inquiry.
Kirkpatrick's Four-Level Training Evaluation Model provides a comprehensive framework for assessing the effectiveness of instructional materials across multiple dimensions. Each level offers valuable insights into different aspects of the learning experience, contributing to a holistic understanding of the impact of instructional materials.
At Level 1 (Reaction), instructional materials are evaluated based on learners' initial reactions, perceptions, and satisfaction with the content and delivery methods. We’ll receive feedback from our student surveys that support iterative improvement from a reaction perspective. Level 2 (Learning) assesses whether learners have acquired knowledge, skills, and attitudes due to the instruction. Our pre/post-test approach should support the measurement of content mastery. Level 3 (Behavior) measures instructional materials based on learners' ability to apply their newly acquired knowledge and skills in real-world settings. Each instructional module's “Do” component should provide a meaningful pathway to demonstrate the desired behavior.
Finally, at Level 4 (Results), the overall impact of instructional materials on organizational outcomes and performance metrics is evaluated. We do not have any data capture built into the courseware that measures the change in behavior across a faculty member’s courses. Ideally, LMS data between our course and the courses created by our students could be shared and presented in a central reporting dashboard. This would demonstrate achievement of the larger organizational goal of augmenting University courses through the creation of introductory videos.
As I conclude this reflection, instructional design's dynamic and transformative nature comes to the forefront. In navigating our journey, I have gleaned insights into the intricacies of alignment, the iterative design process, and the power of collaboration. Each time we work through this process, we learn something new about the science and art of learning design. I am committed to crafting instructional materials that inspire, empower, and resonate with learners. This project has honed my skills and prepared me to meet that goal.
References:
Mager, R. F. (1997). Preparing instructional objectives: A critical tool in the development of effective instruction. The Center for Effective Performance. Garrison, D. R., Anderson, T., & Archer, W. (2000). Critical inquiry in a text-based environment: Computer conferencing in higher education. Internet and Higher Education, 2(2-3), 87-105. Kirkpatrick, D. L. (1996). Evaluating training programs: The four levels. Berrett-Koehler Publishers. Park, S. (2018). Motivation Theories and Instructional Design. In R. E. West (Ed.), Foundations of Learning and Instructional Design Technology. EdTech Books. https://edtechbooks.org/lidtfoundations/motivation_theories_and_instructional_design