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The Hybrid Artifact-Based Framework:

A Review of the Literature

‍ By

‍Melvin Harris

‍Lamar University

‍July 7, 2026

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Introduction

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Education in Texas has seen the rise in the importance of Career and Technical Education classes in recent years to prepare students for college, careers, and industry, and this attention to College, Career, and Military Readiness (CCMR) accountability has placed increased emphasis on using sound instructional practices to develop technical skills, improve Industry-Based Certifications (IBCs), and increase positive student outcomes. Schools are even accelerating, double-blocking, and augmenting their classes and schedules to five a day to increase instructional time and ensure students earn CCMR points as quickly and definitively as possible. In programs such as AV production, students must interact with digital software, online Learning Management Systems (LMS), and various production tools to mirror professional practice and create content that meets myriad standards and TEKS. In these classes, there must be a balance among effective teaching, skill acquisition, and time for students to perform well on the Adobe Certified Expert exam, which serves as the primary mechanism for their certification and, as such, the primary accountability driver. At North Shore Senior High School in Houston, TX, the school district has implemented both accelerated classes and a 5x5 schedule. This creates a myriad of issues in instructional design.

In recent years, the quality of one-to-one digital instruction has been called into question.  These highly technology-enabled classrooms and vast digital environments often replace the time-tested traditional learning strategies that have been effective for decades. Even with increased access to digital instruction, there is strong evidence that reading physical texts, taking notes by hand, and creating physical artifacts can provide prime conditions for durable learning, improved student comprehension, and increased long-term retention. This matters because the AV classroom is essentially all technology, all the time. Even the products and assessments are technology-based, so how can teaching grounded in cognitive science and existing in physical form be used to improve student outcomes while still fitting within the time constraints of teaching an entire year-long class in a single semester?

There is another approach, one that educational research suggests strengthens student retention through generative learning, retrieval, and integrated technology that intentionally combines physical artifacts, such as handwritten notes, printed texts, sketches, and planning documents, with digital artifacts, like multimedia projects, digital portfolios, collaborative documents, and authentic media productions. Rather than treating traditional and digital learning as competing instructional models, the Hybrid Artifact-Based Learning Framework views them as complementary components of the same cognitive process. The purpose of this literature review is to examine the existing research, if any, related to this Learning Framework and explore its theoretical foundations, instructional advantages, implementation, challenges, and how it can be applied within an AV classroom to improve outcomes on an EOC certification exam. It also seeks to answer the research question: How does implementing a Hybrid Artifact-Based Learning model affect students' knowledge retention on Adobe certification exams in my digital media course?

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Review of the Literature

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Definition of The HABL Framework

Hybrid Artifact-Based Learning (HABL) is an instructional framework that purposefully integrates physical and digital artifacts throughout the learning cycle to increase students' understanding, retention, and application of knowledge and skills. The theoretical foundation of HABL is grounded in constructivist learning theory, which holds that learners actively construct knowledge through significant experiences rather than passively receiving information. Within this framework, an artifact is any meaningful product created by a learner that provides evidence of thinking, learning, or skill development. Generative learning theory supports this and expands the definition by suggesting that students learn more effectively when they actively generate meaning through activities that require them to process information more deeply rather than merely memorize facts (Fiorella and Mayer, 2015). Cognitive psychology research also contributes to defining HABL by supporting the assertion that information is more likely to be retained when learners actively manipulate content rather than passively consume it (Dunlosky et al., 2013). Also, Craik and Lockhart (1972) argued that retention depended on aspects of study time, the amount of material presented, and the modality of assessment, as well as on the familiarity, compatibility, and meaningfulness of the material. They also state that retention is a function of depth. Information that is processed deeply through meaningful engagement (deep semantic processing vs. shallow structural processing, i.e., the meaning of words vs. the words themselves or their sounds), organization, rehearsal, and elaboration is more likely to be retained than information processed at a superficial level (Craik & Lockhart, 1972). All of these support the conclusion that HABL is a framework built on sound cognitive principles and designed to maximize student retention.

Components of The HABL Framework

Physical Artifacts:

Physical artifacts, annotated textbooks, Cornell notes, graphic organizers, concept maps, journals, sketches, storyboards, and written reflections are tangible products that students create through direct interaction with printed materials or by producing handwritten work. Research consistently indicates that writing notes by hand promotes deeper processing than verbatim transcription, as students must decide what information is important and organize ideas into meaningful structures (Mueller & Oppenheimer, 2014). This is important for encoding, which is a foundational concept in the HABL Framework. According to Brunsman and McEntarffer (2023), encoding consists of the cognitive processes that occur during learning and influence what information is ultimately stored in long-term memory. In a seminal work on cognitive psychology and memory, Craik and Lockhart (1972) argued that retention depended on aspects of study time, the amount of material presented, and the modality of assessment, as well as on the familiarity, compatibility, and meaningfulness of the material. This means of encoding information is associated with higher levels of remembering. Using physical artifact creation strategies such as annotation, written reflection, sketching, and storyboarding is an effective way to strengthen long-term memory and support conceptual understanding because students imbue these strategies with meaning, and they encourage elaboration and retrieval.

Digital Artifacts:

Digital artifacts such as multimedia presentations, videos, podcasts, websites, collaborative documents, digital portfolios, graphic designs, animations, and other technology-enhanced products are created using technology and demonstrate student understanding through application, providing authentic opportunities to apply knowledge, skills, and techniques. The HABL framework is most closely related to the TPACK (Technological Pedagogical Content Knowledge) framework. According to Koehler et al. (2013), “the TPACK framework describes the kinds of knowledge that teachers need in order to teach with technology, and the complex ways in which these bodies of knowledge interact with one another.” They go on to say that teaching is a context-bound activity and that teachers with developed TPACK use technology to design learning experiences tailored to specific pedagogies, content, and learning contexts (Koehler et al., 2013). TPACK focuses on teachers' planning and decision-making in technology-assisted lesson design, while HABL is a learning-process framework. Therefore, technology serves four functions: Documentation, which includes e-portfolios; Content or learning management systems; Collaboration, which can include shared documents and peer review; Iteration that is engaging and fun, like revision histories or multimedia production; and Feedback, which includes digital assessments and analytics dashboards. Digital artifacts fall under documentation, collaboration, and iteration, and educational technology is leveraged to create content and products that build upon and bolster the physical component.

‍ ‍Hybrid Instructional Sequences:

The main characteristic of HABL is the intentional use and sequencing of both physical and digital artifacts throughout the instructional cycles. It aligns with Generative Learning Theory. Fiorella and Mayer (2015), in their book Learning as a Generative Activity: Eight Learning Strategies that Promote Understanding, explain that students learn more deeply when they generate meaning through activities such as summarizing, mapping, drawing, explaining, and note-making. They must make sense of the material that is given to them. This is accomplished through three cognitive processes, selecting, organizing, and integrating, which move presented information from the sensory memory of just experiencing it with eyes and ears, to working memory, which comes from active attention, recognition, and organization in a coherent cognitive structure, to long-term memory, which involves connecting the other processes and structures with each other and prior knowledge stored there (Fiorella and Mayer, 2015). Rather than choosing between traditional and technology-based instructional practices, the HABL framework leverages the strengths of both to create multiple instances of the outcomes, leading to deep encoding, durable retrieval, transfer, and authentic demonstration of learning on certification assessments. This framework provides an integration model that leverages the advantages of these different artifacts, serving distinct cognitive processes while melding instructional processes.

Advantages of Using HABL

The literature in this review supports the conclusion that students learn more and do so more effectively when they actively construct knowledge and generate meaning rather than simply receive and copy information. HABL promotes this by requiring the students to create artifacts to externalize their thinking and reflect on their understanding. This moves instruction beyond lectures, demonstrations, and tutorials. When students repeatedly generate meaningful artifacts that represent what they think and understand, they engage in deeper cognition and understand more at a conceptual level. Dunlosky et al. (2013) identified retrieval practice, elaborative interrogation, distributed practice, and self-explanation as among the most effective evidence-based learning strategies available to educators.

Many of these strategies naturally arise when students create something, such as artifacts. More and more research highlights the importance of handwritten note-making in improving comprehension and retention. Note-making is very different from note-taking. Note-taking is transcribing information, while note-making is the synthesis, identification, and organization of information using one's own words and pictures. Mueller and Oppenheimer (2014) found that students who created handwritten notes had a more substantial understanding than students who primarily used laptop note-taking, implying that processes occurring during handwriting encourage deeper cognitive processing.

‍HABL also reflects current views of effective technology integration by highlighting that technology should support sound pedagogy rather than guide instructional decisions. The TPACK framework posits that meaningful technology integration happens when teachers thoughtfully integrate technological knowledge with pedagogical and content knowledge (Mishra & Koehler, 2008). Koehler and Mishra (2008) also say that the specific technologies are best suited for addressing subject-matter learning, and how the content drives or perhaps even changes the technology, or vice versa, must be understood. A defining characteristic of HABL is its view of learning as an artifact ecosystem. Rather than treating individual assignments as isolated daily independent work, the framework emphasizes connections among artifacts created throughout the learning process. As a result, the educational technology used must align with whatever is used to produce the artifacts.

‍HABL embraces and mixes each approach to leverage the strength of both modalities. This balance is invaluable in AV classes because students must simultaneously master academic content knowledge, technical skills, and workforce essentials. It becomes a comprehensive framework that supports learning, which has been infused with meaning, and authentic performance on the Adobe ACP exam. This makes it especially well-suited for test prep and for improving student outcomes on IBCs.

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Barriers to Implementing HABL

Despite the substantial evidence supporting the blending of traditional learning strategies with technology within this framework, there are several barriers to implementing HABL in classrooms today. One of the most significant challenges is the overreliance on one-to-one technology integration initiatives that were carried over from COVID protocols. Schools have expanded access to laptops, tablets, and cloud-based educational solutions, moving classrooms from paper-based to exclusively digital formats. This mass adoption has led to a massive debate on the superiority of one method over the other. The cost of implementation has also meant that already-stressed, minuscule budgets have been diverted to technology, and paper-based methods, even photocopying allotments, have been further choked off. This has led to fewer and fewer opportunities for students to engage in evidence-based, hand-written educational experiences.

‍Another barrier to HABLs implementation is the simple fact that educators may not understand how to use technology to produce artifacts that align with the framework’s standards. Although teachers are expected to incorporate district-selected and aligned digital tools into daily instruction, technology integration frameworks emphasize that practical implementation depends on teaching, not just on the technology itself. Again, Koehler et al. (2008) TPACK framework argues that technology produces truly meaningful learning only when it is purposefully aligned with instructional procedures and relevant content. Usually, this would be addressed through relevant PD, but professional development is often focused on learning new software tools or LMS platforms rather than understanding the techniques and cognitive mechanisms by which technology can complement their instruction.  As a result, teachers emphasize usage, completion, and convenience rather than deep thinking, understanding, and retrieval. 

‍There are also practical constraints in the classroom that present their own challenges to using this framework. Developing the artifacts in a meaningful and thoughtful way requires adequate planning and class time, access to resources, and administrative support. When operating under pacing guides, benchmarks, testing schedules, and CCMR deadlines, the assumption is that there isn’t enough time to devote to artifacts, or that the products the class creates are plenty. This barrier is specifically what spurred the research. In CTE, students are expected to master the complex applications of highly technical software to perform well on IBC assessments. There is enormous pressure to maximize screen time for test prep rather than take precious time away from that to annotate, reflect, or create handwritten products. Using HABL successfully means being careful and deliberate in instructional design and integrating it into existing lessons rather than treating it as a completely new endeavor or creating extra supplemental assignments. 

‍Finally, there is limited evidence that combining handwritten note-making, student-generated artifacts, authentic project-based learning, and technology integration actually improves performance on IBCs. Most of the modern consensus on improving student outcomes on these assessments focuses on curriculum, proficiency with the specific software, or practice testing, rather than student learning. This gap is evident in CTE classrooms where student success depends on conceptual and technical competence. This action research study seeks to address this gap directly by coupling supporting research with student performance on G-Metrix practice assessments, Adobe Certified Professional examination scores, and certification pass rates. Measuring these outcomes qualitatively and examining the results should inform evidence-based guidance for teachers seeking instructional approaches that build IBC readiness while preserving the cognitive benefits associated with the framework.

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Hybrid Artifact-Based Learning and Adobe Certification Success

AV Production classes are in a unique position within secondary education because student success is measured not only through achievement but also through workforce readiness and the attainment of Industry-Based Certification to increase accountability for College, Career, and Military Readiness. The Adobe Certified Professional certification, the main driver of CCMR adherence, requires students to integrate conceptual knowledge, specific procedures, and problem-solving skills under conditions that stress timeliness, accuracy, and efficiency. Preparing for this exam has long emphasized repeated rote practice, online tutorials, and simulated testing environments such as G-Metrix. These resources give students practical opportunities to become familiar with the exam and its objectives. However, research from this review suggests that long-term learning requires more than this. Digital practice environments may not be enough to fully leverage strategies proven to build durable learning. The Hybrid Artifact-Based Learning Framework offers an approach to certification prep that closely aligns with the cognitive principles underlying generative learning and provides multiple opportunities for students to boost their learning before taking expensive, high-stakes certification assessments.

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Summary

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The Hybrid Artifact-Based Learning Framework offers an approach to certification prep that closely aligns with the cognitive principles underlying generative learning and provides multiple opportunities for students to boost their learning before taking expensive, high-stakes certification assessments.

‍Research from cognitive psychology, generative learning, and technology integration consistently demonstrates that strategies requiring learners to organize, retrieve, explain, and apply prior and acquired knowledge promote deeper understanding and long-term retention more than activities primarily focused on memorizing and consuming lectures, demonstrations, or slide presentations.

Within the HABL framework, students may annotate printed instructional materials, create handwritten Cornell or 3R notes, develop concept maps, sketch interface layouts, storyboard projects, or write reflections explaining design decisions. These physical artifacts require students to organize information and synthesize concepts to apply their knowledge within Adobe Creative Cloud applications. Then, the students transition to creating digital media projects, portfolios, and original productions, repeatedly retrieving and applying previously acquired knowledge while receiving feedback through both classroom instruction and digital practice platforms.

‍This body of literature provides a strong theoretical foundation for these practices. It supports different stages of the learning process and identifies an important gap in existing practices regarding how these strategies influence IBC outcomes in an AV class.

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This Review and the Field of Education

‍This review contributes to the field of education by synthesizing research across several areas that are often examined independently. Studies investigating physical artifact creation and encoding, technology integration, and project-based learning each provide insights into effective instructional practice, but few have examined how these approaches synergize into a single framework that supports instruction. HABL extends existing research by proposing that the physical and digital artifacts do not compete, but complement each other to support different aspects of thinking and development. This is important as schools continue to expand digital learning and seek methods to improve learning rather than just technology use. 

‍This important study connects learning science with CTE and the AV classroom. Much of the research in this study focuses on general education settings, but CTE classrooms are unique in that they require students to master technical skills, creative problem-solving, and core workplace competencies. As CCMR accountability is increasingly emphasized, frameworks like HABL may become much more valuable for educators, regardless of the discipline they teach.

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Strengths and Weaknesses of this Body of Literature

One of the greatest strengths of this literature is the consistency with which researchers support active learning as a means for improvement and achievement. All studies in cognitive psychology, educational technology, and instructional design consistently conclude that learners retain information more effectively when they actively organize, retrieve, explain, and apply knowledge rather than passively receive it. Strong practical and empirical support exists for handwritten note-making, retrieval practice, generative learning, and authentic project-based learning, while technology integration frameworks such as TPACK provide recommendations for implementing digital tools in pedagogically significant ways. Because these findings are abundant across multiple strands of research, they collectively provide a sound foundation for the principles and components underpinning HABL.

‍However, lingering limitations remain in the existing research literature. Most studies examine the components and practices of HABL in a vacuum rather than interrogating the processes that blend these strategies into a unified framework. This is a weakness. Also, few studies have examined these practices in CTE classrooms, and even fewer apply to AV Production classes. Research on the Adobe ACP test and prep is also extremely limited, and much of the literature focuses specifically on software proficiency or curriculum alignment. Therefore, educators have very little evidence regarding the structural integrity of an argument for a framework like HABL. This presents an opportunity for further research, but it remains a significant weakness nonetheless, as there is no bridge connecting theory and practice in the literature.

Focus of the Current Study

The current action research study builds upon the literature reviewed by investigating whether HABL can improve student performance on the Adobe ACP exam. Existing research strongly supports many of the individual instructional strategies incorporated into HABL, but limited research has examined whether combining these practices in AV will yield measurable improvements. This study seeks to directly address that gap by implementing a solution that combines the most salient practices identified in the research. Student performance will be measured with qualitative data, including G-Metrix practice assessment scores, teacher-created benchmark assessments, project rubric scores, official Adobe Certified Professional examination scores, and certification pass rates. There is evidence that these findings will contribute to the growing body of research on instructional strategies in CTE and provide practical guidance for teachers and administrators seeking to improve IBC outcomes and CCMR accountability through evidence-based instructional design.

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References

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Brunsman, B., & McEntarffer, R. (2023, February 23). Memorable feedback: Lessons from cognitive psychology in encoding. The Learning Scientists. https://www.learningscientists.org/blog/2023/2/23-1

Craik, F. I. M. (2002). Levels of processing: Past, present... and future? Memory, 10(5–6), 305–318

Diemand-Yauman, C., Oppenheimer, D. M., & Vaughan, E. B. (2011). Fortune favors the bold (and the italicized): Effects of disfluency on educational outcomes. Cognition, 118, 111–115

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Dunlosky, J., Rawson, K. A., Marsh, E. J., Nathan, M. J., & Willingham, D. T. (2013). Improving students' learning with effective learning techniques: Promising directions from cognitive and educational psychology. Psychological Science in the Public Interest, 14(1), 4–58. https://doi.org/10.1177/1529100612453266

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Fiorella, L., & Mayer, R. E. (2015). Learning as a generative activity: Eight learning strategies that promote understanding. Cambridge University Press.

Hughes, J. E., & Roblyer, M. D. (2022). Integrating Educational Technology Into Teaching: Transforming Learning Across Disciplines. Pearson.

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Koehler, M. J., Mishra, P., Akcaoglu, M., & Rosenberg, J. M. (2013). The technological pedagogical content knowledge framework for teachers and teacher educators. In M. Herring, M. J. Koehler, & P. Mishra (Eds.), ICT integrated teacher education models (pp. 1–8). Commonwealth Educational Media Centre for Asia (CEMCA).

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Mueller, P. A., & Oppenheimer, D. M. (2014). The pen is mightier than the keyboard: Advantages of longhand over laptop note taking. Psychological Science, 25(6), 1159–1168. https://doi.org/10.1177/0956797614524581

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