Is TPACK framework effective for Executive Coaching?
Reference:
Harris, J., & Hofer, M. (2011). Technological pedagogical content knowledge (TPACK) in action: A descriptive study of secondary teachers’ curriculum-based, technology-related instructional planning. Journal of Research on Technology in Education, 43(3), 211–229. https://doi.org/10.1080/15391523.2011.10782570
Annotation:
Judith Harris and Mark Hofer (2011) examined how experienced teachers plan instruction that effectively integrates technology with content and pedagogy. Through qualitative interviews, unit analyses, and reflective journals, the researchers found that teachers’ use of technology became more conscious, strategic, and student-centered after participating in professional development focused on content-based “learning activity types.” Teachers began selecting technologies not for their novelty but for how well they served learning goals, demonstrating that effective integration requires understanding the nuanced “fit” between tools, content, and learners.
The study introduced a replicable framework for developing adaptive expertise through reflective planning and design thinking principles that extend far beyond education - hence why it is relevant to executive coaching!
For leadership and management consultants, Harris and Hofer’s study offers a powerful parallel to the challenges of coaching and organizational learning. Their methodology is deeply interpretive, reflective, and evidence-based which mirrors the way executive coaches guide leaders through awareness, experimentation, and refinement. By mapping how teachers evolve from “technocentric” to “learner-centric” thinking, the research models how leaders can move from “tool orientation” (e.g., implementing AI dashboards or engagement platforms) to behavioral fluency like integrating technology with strategy, culture, and context.
The study’s TPACK framework can be adapted for leadership enablement, where:
content = strategy
pedagogy = leadership approach
technology = tools
These facilitate decision-making and communication. HR professionals can use this lens to design more effective coaching interventions shifting from system implementation to skill integration, much like educators learned to shift focus from software features to meaningful outcomes.
Traditional Executive Coaching example:
Coach: “You’ve mentioned frustration with your team’s resistance to the analytics platform. What emotions come up for you when you see that resistance?”
COO: “It feels like they’re not moving fast enough, like they’re clinging to old ways.”
Coach: “What leadership behaviors could help model the adaptability you’d like to see?”
COO: “Maybe I could be more transparent about my learning curve too.”
Coach: “Excellent. Let’s develop a communication plan that frames your learning story and sets expectations.”
Result: The coach helps the leader become more self-aware, emotionally intelligent, and strategic in communication, but the technology integration challenge remains largely unaddressed.
TPACK Framework Executive Coaching Example:
Coach: “You’re leading a transformation that depends on your team’s ability to use data strategically. Let’s explore how your communication methods and tool use align with that goal.”
COO: “I’ve asked them to adopt the dashboard, but they still default to old reports.”
Coach: “That’s an example of a content-technology gap. What if we designed learning sessions that focus not just on using the tool but on interpreting data for strategic decisions? You could co-facilitate those sessions modeling the kind of data-driven thinking you expect.”
COO: “That makes sense. I can use our next operations meeting to walk through how I’m using the data for forecasting.”
Coach: “Exactly. That integrates the technology into your leadership pedagogy turning the tool into a platform for shared sense-making, not compliance.”
Result: The coaching moves from personal reflection to adaptive system design aligning how the leader teaches, communicates, and models behavior through the actual technology being adopted.
Coach’s Focus:
Technology = digital tools and data systems being implemented.
Pedagogy = the coaching approach or facilitation method (how the leader learns).
Content = the business strategy, goals, or leadership outcomes being developed.
Try using AI Personalized Podcasts to Drive Retention & Employee Development
Reference:
Do, T. D., Bin Shafqat, U., Ling, E., & Sarda, N. (2024). PAIGE: Examining learning outcomes and experiences with personalized AI-generated educational podcasts (arXiv preprint arXiv:2409.04645). https://doi.org/10.48550/arXiv.2409.04645
Annotation:
The researcher take a deep dive into how generative AI can convert textbook chapters into personalized educational podcasts for a group of 180 college students. The researchers compared traditional textbook reading with both generalized and personalized AI-generated podcasts across multiple subject areas. Their findings showed that students overwhelmingly preferred podcasts to reading, and that personalized podcasts tailored to learners’ backgrounds and interests improved comprehension in several disciplines.
The takeaway is clear: AI-driven, personalized audio content can enhance learning engagement and outcomes when designed with relevance and learner context in mind.
The study’s methodology, integrating AI-driven podcast generation with validated user experience measures, models exactly the kind of data-informed experimentation L&D professionals can use to evaluate their own digital learning tools. It also underscores the importance of delivery design, such as the conversational tone, pacing, and modality that can have a deep influence in learner motivation. Consultants working with clients on upskilling strategies can take from this that AI isn’t just a content generator; it’s an adaptive facilitator that can align learning experiences to individual needs and organizational culture.
At Allegiant, our consulting work centers on helping organizations create inclusive learning environments that make workplace learning more effective for all employees, particularly those whose neurodivergence offers unique cognitive strengths. Studies like this one inform how we think about designing micro-learning and leadership development content that doesn’t just “teach,” but connects meaningfully with how diverse minds engage with information.
We also see a connection between this research and how business leaders who host industry podcasts can influence engagement and retention. A 2023 LinkedIn Workplace Learning Report found that employees who feel connected to their organization’s thought leadership (through podcasts or leadership-led storytelling) are 33% more likely to stay with the company. Integrating AI-generated podcasts or internal learning channels can give employees that same sense of inclusion and relevance.
As our research and consulting practice evolves, we’re exploring how personalization, audio learning, and neurodivergent engagement strategies can converge to make corporate learning both equitable and deeply human.
Using Storytelling and AI Podcasts to Unlock the Power of Neurodiverse Learning
Reference:
Hung, C.-M., Hwang, G.-J., & Huang, I. (2012). A Project-based Digital Storytelling Approach for Improving Students' Learning Motivation, Problem-Solving Competence and Learning Achievement. Educational Technology & Society, 15(4), 368–379.
Annotation:
Hung, Hwang, and Huang (2012) explore how blending project-based learning (PBL) with digital storytelling (DST) can transform students’ engagement and performance in science education. Conducted with 117 fifth-grade students in Taiwan, the study found that students who learned through digital storytelling exhibited significantly higher learning motivation, problem-solving competence, and academic achievement than those who participated in traditional project-based instruction. The research demonstrated that combining structured inquiry with creative expression enhances both comprehension and emotional connection to learning.
What makes the Hung study particularly compelling is its methodical approach. The quasi-experimental design, with both pre- and post-tests, allowed for robust comparisons between groups and yielded quantifiable evidence of learning gains. The use of validated scales for measuring motivation and problem-solving competence strengthened reliability, while the incorporation of student interviews added valuable qualitative depth.
While Hung et al. grounded their study in the K–12 context, the implications extend naturally to adult workplace learning, particularly in environments striving to leverage neurodiverse talent. The 2024 study “PAIGE: Examining Learning Outcomes and Experiences with Personalized AI-Generated Educational Podcasts” (Do, Shafqat, Ling, & Sarda) complements Hung’s findings by showing how AI-generated podcasts can personalize learning experiences, improving retention and motivation among adult learners. Together, these studies underscore a key insight for organizations: personalization and storytelling are powerful equalizers in learning.
For neurodivergent professionals, who often think visually, narratively, or auditorily, these project-based tools for storytelling or adaptive podcasts can transform potential “differences” into competitive strengths. At our firm, we help organizations design inclusive learning ecosystems that combine these principles: using narrative frameworks to engage emotion and AI to tailor pacing, modality, and delivery to individual cognitive profiles. The next frontier of workplace learning isn’t just digital — it’s deeply human, driven by empathy, adaptability, and design thinking that turns neurodiversity into innovation.
The Impact of Choice in Learning
Reference:
Murphy, J., Farrell, K., & Myers, J. (2024). Student choice in online asynchronous higher education courses. In Proceedings of the [Conference Name if known]. ACM. https://doi.org/10.1145/3760213.3708894
Annotation:
The article explores how offering students choices in online asynchronous higher education courses enhances engagement, autonomy, and relevance. Drawing from theories like constructivism, self-determination, and andragogy, the authors argue that allowing flexibility in content, process, and product supports deeper learning and motivation. A pilot study with undergraduate and graduate students found that choice particularly strengthened connections to career goals, encouraged authentic learning experiences, and increased satisfaction. The findings suggest that structured opportunities for choice can transform courses into learner-centered environments that foster agency, self-regulation, and practical application.
Murphy, Farrell, and Myers (2024) does a good job of clearly connecting theory to practice by showing how student choice can improve engagement in online learning. The use of a pilot study with both undergraduates and graduate students gives it a practical angle that helps support the claims, even if the sample size is modest. The mix of quantitative survey results and qualitative student feedback adds depth and makes the findings feel more grounded. Overall, the article is well organized and easy to follow, making complex ideas accessible without being overly technical.
The ideas in this article translate well into workplace training and curriculum design because they highlight the importance of giving adults meaningful choices in how they learn. In professional settings, employees bring diverse experiences, learning preferences, and career goals, so offering flexibility in content, process, and product can make training more relevant and motivating. The emphasis on autonomy and authentic application resonates strongly with adult learning in the workplace, where practical connections often matter more than abstract theory. This approach supports consultants and trainers in creating programs that not only build skills but also encourage ownership, engagement, and long-term growth.
Perception drives Interpretation of Feedback
Reference:
Newman, D. (2025). Examining the emotional tone of student evaluations of teaching. Canadian Journal of Learning and Technology, 51(1), 1–18. https://doi.org/10.21432/CJLT-28695
Annotation:
How does perception affect feedback? Newman (2025) analyzed 600 student-written evaluations from Rate My Professors (2018–2023) to determine the emotional tone of the language used. Students feedback was reviewed using indicators such as pleasantries and words with positive connotations using Whissell’s Dictionary of Affectionate (DOA). The study found that students provided feedback to instructors in the evaluations that were emotionally neutral in tone however, the instructors perceived the tone to be overly critical on average.
The study’s strengths lie in the reliability of the tools used, like the DOA, and the simplicity of how the study is measured. The correlations are easy to understand and the study itself and its methods are easy enough to understand that replication can be completed with ease. Newman (2025) also provided adequate acknowledgements to the limitations of the information reviewed such as sampling bias, word count variability, and the constraints of publicly available online data.
In the context of organizational performance management, this article underscores the value of distinguishing emotional perception from objective data. Similar to how faculty may overinterpret student comments as overly negative, employees and managers often perceive performance evaluations as more emotionally charged than they actually are. For consultants, the findings point to the importance of designing evaluation systems that emphasize neutrality and balance. By integrating structured training on how to give and receive feedback, organizations can foster a shared understanding that feedback is a tool for growth rather than criticism. Embedding “feedback literacy” into workplace practices not only reduces defensiveness and bias but also equips both leaders and staff with the skills to interpret evaluations constructively. This approach supports the development of resilient, evidence-based performance systems that encourage trust, reduce anxiety, and create a culture where feedback is seen as an essential driver of individual and organizational improvement.