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A Scoping Review to Explore How Decision-Making Is Discussed in the Field of Learning Design

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Title: A Scoping Review to Explore How Decision-Making Is Discussed in the Field of Learning Design
Language: English
Authors: Jill Stefaniak (ORCID 0000-0002-9571-9215), Meimei Xu, Fan Yang
Source: TechTrends: Linking Research and Practice to Improve Learning. 2025 69(4):714-722.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 9
Publication Date: 2025
Document Type: Journal Articles
Information Analyses
Descriptors: Instructional Design, Decision Making, Educational Technology, Educational History, Professional Development, Educational Research
DOI: 10.1007/s11528-025-01053-5
ISSN: 8756-3894
1559-7075
Abstract: Instructional design practices consist of design decisions. It often comprises decisions across analysis, design, development, implementation, and evaluation. This paper presents the findings of a scoping review that explored how decision-making is discussed in learning design research over the past four decades. This scoping review of research investigates conceptual papers and empirical studies that discussed decision-making in instructional design and/or educational technology contexts. The sample covers research published over four decades (1990-2023). By gaining an understanding of how decision-making is investigated and discussed in different contexts of educational technology, the field is positioned to support designers in the field as well as throughout their professional development.
Abstractor: As Provided
Entry Date: 2025
Accession Number: EJ1480224
Database: ERIC
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  Value: <anid>AN0187262891;ttr01jul.25;2025Aug13.05:37;v2.2.500</anid> <title id="AN0187262891-1">A Scoping Review to Explore How Decision-Making is Discussed in the Field of Learning Design </title> <p>Instructional design practices consist of design decisions. It often comprises decisions across analysis, design, development, implementation, and evaluation. This paper presents the findings of a scoping review that explored how decision-making is discussed in learning design research over the past four decades. This scoping review of research investigates conceptual papers and empirical studies that discussed decision-making in instructional design and/or educational technology contexts. The sample covers research published over four decades (1990–2023). By gaining an understanding of how decision-making is investigated and discussed in different contexts of educational technology, the field is positioned to support designers in the field as well as throughout their professional development.</p> <p>Keywords: Decision-making; Instructional design; Instructional designers</p> <p>Copyright comment Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.</p> <hd id="AN0187262891-2">Introduction</hd> <p>Instructional design practices consist of design decisions. It often comprises decisions across analysis, design, development, implementation, and evaluation. Prior researchers have addressed instructional design as one kind of real-world problem-solving (Jonassen, [<reflink idref="bib19" id="ref1">19</reflink>]). Design problems are often ill-structured due to its dynamic nature: instructional designers need to make a variety of design decisions for instructional design, drawing from their prior experiences, knowledge, skills, and environmental factors that influence the learning environments. Instructional design decision-making thereby requires instructional designers to recognize the unstructured nature of the design space and utilize design conjecturing and reflective strategies to make decisions.</p> <p>Decision-making has been categorized into two types: rational and dynamic (Jonassen, [<reflink idref="bib19" id="ref2">19</reflink>], [<reflink idref="bib20" id="ref3">20</reflink>]; Klein, [<reflink idref="bib24" id="ref4">24</reflink>]). While rational decision-making emphasizes a series of procedural actions to help decision-makers make a decision; dynamic decision-making, also named as naturalistic decision-making, highlights short time frames in which decisions are made within a dynamic, contextualized, and unstructured learning environment. Instructional design decision-making often involves both rational decision-making and dynamic decision-making processes. Rational decision-making provides instructional designers with enough time and resources to compare different options, conduct analyses, and make decisions. Comparably, dynamic decision-making entails instructional designers to have an awareness of the environmental factors influencing the learning contexts and the affordances within the learning space (Webb & Cox, [<reflink idref="bib39" id="ref5">39</reflink>]).</p> <p>Dynamic decision-making supports instructional designers as decision-makers to make design decisions based on a systematic analysis of factors that enable instructional designers to transfer knowledge from the learning environment into a real-world unstructured context (Stefaniak & Xu, [<reflink idref="bib36" id="ref6">36</reflink>]). A typical scenario of dynamic decision-making is how instructional designers make prompt decisions for the transfer from face-to-face classroom learning to online learning due to the recent global health crisis. As a result of short time frames and a variety of contextual factors such as student learning needs, students' knowledge and capabilities, technologies, subjects of knowledge, budget, time constraints, and corresponding educational policies, instructional designers need to rely on their perceptions towards the contextual variables within the real-world contexts, and to implement dynamic decision-making for the construction of online learning environments.</p> <p>Another relevant concept is dynamic decision-making within a bounded rationality (Simon, [<reflink idref="bib32" id="ref7">32</reflink>]). This conception indicates how practitioners rationalize their decisions to solve ill-structured problems or within an unstructured environment. While rational decision-making is also involved in instructional designers' decision-making in some ways, dynamic decision-making plays the major role in their decision-making processes, as it helps instructional designers establish and make prompt decisions within a bounded rationality to rationalize their instructional design decisions.</p> <p>Scholars in the field of instructional design complemented that the decision-making processes in instructional designers also comprise instructional design judgments that enable instructional designers or practitioners to recognize the ill-structured design problems and come up with a comparably ideal design solution (Lachheb & Boling, [<reflink idref="bib26" id="ref8">26</reflink>]; Nelson & Stolterman, [<reflink idref="bib29" id="ref9">29</reflink>]). While dynamic decision-making puts more focus on how practitioners leverage a variety of environmental factors and make corresponding adjustments, instructional design judgments emphasize the role of internal conjectures and flexibilities in instructional designers that help with their decision-making processes (Lachheb & Boling, [<reflink idref="bib26" id="ref10">26</reflink>]).</p> <p>Thus, instructional design decision-making is a complex, contextualized, and ill-structured process with multiple constructs and variables. Here, we present an overview of the decision-making models and frameworks discussed in the field of educational technology and instructional design. Table 1 lists all the decision-making models and frameworks indicated in educational technology research studies. We also included the description of all the decision-making models or frameworks in the table.</p> <p>Table 1 Different decision-making models/framework and supporting literature</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Decision-making model</p></th><th align="left"><p>Description</p></th></tr></thead><tbody><tr><td align="left"><p>The conceptual framework supporting learning design in the digital environment (Stefaniak et al.,, <xref ref-type="bibr" rid="bibr35">2021</xref>)</p></td><td align="left"><p>A framework that describes how pedagogical reasoning and dynamic decision-making support instructional designers make decisions within digital learning environments</p></td></tr><tr><td align="left"><p>The rational decision-making model (Jonassen, <xref ref-type="bibr" rid="bibr19">2010</xref>, <xref ref-type="bibr" rid="bibr20">2012</xref>; Klein, <xref ref-type="bibr" rid="bibr23">1998</xref>)</p></td><td align="left"><p>A procedural framework consisting of eight essential steps for rational decision-making</p></td></tr><tr><td align="left"><p>The recognition-primed decision (RPD) model (Klein, <xref ref-type="bibr" rid="bibr24">2008</xref>)</p></td><td align="left"><p>A model that recognizes contextual factors and the dynamic nature of decision-making context</p></td></tr><tr><td align="left"><p>The situation awareness (SA) model (Endsley, <xref ref-type="bibr" rid="bibr12">1995</xref>)</p></td><td align="left"><p>A model that emphasizes situational factors (external) and internal factors that influence decision-making</p></td></tr><tr><td align="left"><p>The reflective decision-making framework (Tracey et al., <xref ref-type="bibr" rid="bibr37">2014</xref>)</p></td><td align="left"><p>A framework that describes how reflection-in-action can help instructional designers make decisions in various contexts</p></td></tr><tr><td align="left"><p>The teacher response model (TRM) of technology integration (Kopcha et al., <xref ref-type="bibr" rid="bibr25">2020</xref>)</p></td><td align="left"><p>A model that emphasizes teachers' decision-making is a value-driven and learner-centered process hugely relying on teacher perceptions towards technology integration</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0187262891-3">Purpose of Study</hd> <p>Decision-making is inherent in the instructional design process (Gray et al., [<reflink idref="bib15" id="ref11">15</reflink>]; Honebein & Reigeluth, [<reflink idref="bib17" id="ref12">17</reflink>]; Jonassen, [<reflink idref="bib20" id="ref13">20</reflink>]; Lachheb & Boling, [<reflink idref="bib26" id="ref14">26</reflink>]; York & Ertmer, [<reflink idref="bib46" id="ref15">46</reflink>]). While decision-making has been noted as being a critical component to instructional design, often in the peripheral of many papers (i.e., Kerr, [<reflink idref="bib22" id="ref16">22</reflink>]; Reigeluth, [<reflink idref="bib31" id="ref17">31</reflink>]; Wedman & Tessmer, [<reflink idref="bib40" id="ref18">40</reflink>]; Wildman, [<reflink idref="bib41" id="ref19">41</reflink>]), the ways in which designers engage in decisions to support learning design is an area that warrants further exploration. The purpose of this study was to conduct a scoping review to provide an overview of the research and discourse that has surrounded decision-making activities in instructional design. Our rationale for this study was to gain a better understanding of how decision-making is approached in the field, the types of decisions being made, and the relationship between decision-making approaches and project outcomes.</p> <p>By gaining an understanding of how decision-making is applied in different contexts, the field is positioned to support instructional designers in the field as well as throughout their professional development (Boling et al., [<reflink idref="bib6" id="ref20">6</reflink>]; Ertmer et al., [<reflink idref="bib13" id="ref21">13</reflink>]; Honebein & Honebein, [<reflink idref="bib16" id="ref22">16</reflink>]; York & Ertmer, [<reflink idref="bib45" id="ref23">45</reflink>]; Zhu et al., [<reflink idref="bib47" id="ref24">47</reflink>]). In order to examine how decision-making is addressed in the preparation of instructional designers, it is important to explore the span of research on decision-making in the field. Therefore, the following guiding research question and four follow-up questions guided this scoping review:</p> <p>What research has been done on decision-making in the field of learning, design, and technology?</p> <p>Specifically, four research questions guided the review. They were:</p> <p></p> <ulist> <item> In what context are decisions being made (i.e. K-12, healthcare, corporate, etc.)?</item> <p></p> <item> Who are the decision makers?</item> <p></p> <item> What are the types of papers being published related to decision-making (i.e. lit review, qualitative, mixed, quantitative)?</item> <p></p> <item> What types of decisions are made in the papers exploring decision-making?</item> </ulist> <hd id="AN0187262891-4">Methods</hd> <p></p> <hd id="AN0187262891-5">Research Design</hd> <p>We used a scoping review method to address the broad question around what types of research has been conducted related to decision-making in the field of learning, design, and technology. Scoping reviews uses a rigorous systematic process to gain a broad understanding of existing research related to a topic (Arksey & O'Malley, [<reflink idref="bib1" id="ref25">1</reflink>]; Pham et al., [<reflink idref="bib30" id="ref26">30</reflink>]) with the goal that additional studies may stem from the results of our study.</p> <p>Similar to systematic reviews, scoping reviews should adhere to a rigorous process for screening studies to be included in the review study. We used Arksey and O'Malley's ([<reflink idref="bib1" id="ref27">1</reflink>]) six-stage scoping review process and the PRISMA Extension for scoping reviews (Tricco et al., [<reflink idref="bib38" id="ref28">38</reflink>]) to guide our research team through the various phases of screening and analysis. The PRISMA extension is a modification of the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (Moher et al., [<reflink idref="bib28" id="ref29">28</reflink>]).</p> <hd id="AN0187262891-6">Selection Criteria and Screening Process</hd> <p>We followed the PRISMA extension for scoping reviews (Tricco et al., [<reflink idref="bib38" id="ref30">38</reflink>]) to guide our screening and selection process. This also helped our research team ensure rigor in our scoping review. Studies included in this review were published in peer-reviewed journals. Papers published in non-peer-reviewed journals were excluded. Papers included were published in English language journals. Non-English language journals were excluded. The papers also needed to reference decisions or decision-making processes regarding learning design and educational technology.</p> <p>We searched for eligible studies in five databases: Educational Research Information Center (ERIC), APA PsychInfo, EBSCOhost, PubMed, and ABI/INFORM. This yielded a total of 2,351 papers. We did not put any restrictions on articles published earlier, but we did search through 2023. Figure 1 provides an overview of the search terms we used during this initial identification phase of our scoping review. An additional round of searching was conducted using Google Scholar. We reviewed the first 10 pages of results. This yielded an additional 330 papers to be considered. Upon removing duplicates, we were left with 1,719 papers. Our next phase of our screening process was to review the title and abstract of the paper to determine if it met the inclusion criteria for our review. The papers had to reference decisions or decision-making. The results of this round of screening left us with 457 studies. From there we reviewed the full text of the papers based on the inclusion criteria. This resulted in a total of 122 papers that were included in the review.</p> <p>Graph: Fig. 1 The screening process of this scoping review</p> <hd id="AN0187262891-7">Coding</hd> <p>We coded the 122 relevant papers into a spreadsheet according to the following dimensions: year of publication, type of paper (literature review, empirical study), research design, data collection tools, setting, decision-makers, purpose of study, participants, implications for future work on decision-making. Each paper was coded by a member of the research team and reviewed by a second reviewer.</p> <hd id="AN0187262891-8">Results</hd> <p>The scoping review yielded 122 papers related to decision-making in learning design contexts. The section below shows these tables and explanations. We present the following descriptive statistics on research examining decision-making, focusing on publication trends, research methodologies, and contexts. We then provide an overview of the thematic areas explored in decision-making research.</p> <hd id="AN0187262891-9">Trajectory</hd> <p>Figure 2 shows the publication trajectory from 1990 to 2023. The field began to see growth in this area of research after 1990. Since 2010, there has been a steady increase in more papers exploring decision-making as it relates to instructional design.</p> <p>Graph: Fig. 2 Publication trajectory from 1990 to 2023</p> <hd id="AN0187262891-10">Geographic Publication</hd> <p>Table 2 provides an overview of the geographical location of the study's context. A majority of these studies were conducted in North America (83; 68%). This was followed by Europe (21; 17%), Asia (12; 9%), Oceania (5; 4%; and Africa (1; 2%).</p> <p>Table 2 Countries of study</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Continent</p></th><th align="left"><p>Number of articles</p></th><th align="left"><p>%</p></th></tr></thead><tbody><tr><td align="left"><p>North America</p></td><td align="left"><p>83</p></td><td align="left"><p>68%</p></td></tr><tr><td align="left"><p>Europe</p></td><td align="left"><p>21</p></td><td align="left"><p>17%</p></td></tr><tr><td align="left"><p>Asia</p></td><td align="left"><p>12</p></td><td align="left"><p>9%</p></td></tr><tr><td align="left"><p>Oceania</p></td><td align="left"><p>5</p></td><td align="left"><p>4%</p></td></tr><tr><td align="left"><p>Africa</p></td><td align="left"><p>1</p></td><td align="left"><p>2%</p></td></tr><tr><td align="left"><p>Total</p></td><td align="left"><p>122</p></td><td align="left"><p>100%</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0187262891-11">Types of Papers</hd> <p>Table 3 provides an overview of the types of papers included in this review. Among the 122 papers, 85 papers (70%) were empirical studies. Thirty-four studies (28%) were conceptual papers, and three studies (2%) were literature reviews.</p> <p>Table 3 Type of papers</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Category</p></th><th align="left"><p>Number of articles</p></th><th align="left"><p>Percent of articles (%)</p></th></tr></thead><tbody><tr><td align="left"><p>Empirical Studies</p></td><td align="left"><p>85</p></td><td align="left"><p>70%</p></td></tr><tr><td align="left"><p>Conceptual</p></td><td align="left"><p>34</p></td><td align="left"><p>28%</p></td></tr><tr><td align="left"><p>Literature review</p></td><td align="left"><p>3</p></td><td align="left"><p>2%</p></td></tr><tr><td align="left"><p>Total</p></td><td align="left" /><td align="left"><p>100%</p></td></tr></tbody></table> </ephtml> </p> <p>Of the 122 studies included in this scoping review, a total of 85 papers were empirical studies. Table 4 provides an overview of the research design employed in this review. Of the 85 empirical studies, 53 studies (62%) reported using qualitative methods, 27 studies (32%) reported using quantitative methods, and 5 studies (6%) reported using mixed methods.</p> <p>Table 4 Types of empirical studies</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Type</p></th><th align="left"><p>Number of articles</p></th><th align="left"><p>Percent of articles (%)</p></th></tr></thead><tbody><tr><td align="left"><p>Qualitative</p></td><td align="left"><p>53</p></td><td align="left"><p>62%</p></td></tr><tr><td align="left"><p>Quantitative</p></td><td align="left"><p>27</p></td><td align="left"><p>32%</p></td></tr><tr><td align="left"><p>Mixed-Methods</p></td><td align="left"><p>5</p></td><td align="left"><p>6%</p></td></tr><tr><td align="left"><p>Total</p></td><td align="left"><p>85</p></td><td align="left"><p>100%</p></td></tr></tbody></table> </ephtml> </p> <p>Table 5 provides an overview of the contexts of empirical studies included in this scoping review. Several studies were conducted in higher education (46; 54%). This was followed by K-12 (21; 25%), multiple contexts (16; 19%), and healthcare (2; 2%).</p> <p>Table 5 Contexts</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Contexts of empirical studies</p></th><th align="left"><p>Number of articles</p></th><th align="left"><p>%</p></th></tr></thead><tbody><tr><td align="left"><p>Higher education</p></td><td align="left"><p>46</p></td><td align="left"><p>54%</p></td></tr><tr><td align="left"><p>K-12 settings</p></td><td align="left"><p>21</p></td><td align="left"><p>25%</p></td></tr><tr><td align="left"><p>Multiple instructional design disciplines</p></td><td align="left"><p>16</p></td><td align="left"><p>19%</p></td></tr><tr><td align="left"><p>Healthcare</p></td><td align="left"><p>2</p></td><td align="left"><p>2%</p></td></tr><tr><td align="left"><p>Total</p></td><td align="left"><p>85</p></td><td align="left"><p>100%</p></td></tr></tbody></table> </ephtml> </p> <hd id="AN0187262891-12">Themes of Empirical Studies</hd> <p>The empirical studies (n = 85) included in this scoping review were coded and grouped by theme (Table 6).</p> <p>Table 6 Overview of themes</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Overview of themes</p></th><th align="left"><p>Number of articles</p></th><th align="left"><p>%</p></th></tr></thead><tbody><tr><td align="left"><p>Design judgments</p></td><td align="left"><p>24</p></td><td align="left"><p>28%</p></td></tr><tr><td align="left"><p>Pedagogical decision-making</p></td><td align="left"><p>19</p></td><td align="left"><p>22%</p></td></tr><tr><td align="left"><p>Decision-making strategies</p></td><td align="left"><p>16</p></td><td align="left"><p>19%</p></td></tr><tr><td align="left"><p>Technology integration and adaptation</p></td><td align="left"><p>11</p></td><td align="left"><p>13%</p></td></tr><tr><td align="left"><p>Reflective practice</p></td><td align="left"><p>7</p></td><td align="left"><p>8%</p></td></tr><tr><td align="left"><p>Evidence-based decision-making</p></td><td align="left"><p>6</p></td><td align="left"><p>7%</p></td></tr><tr><td align="left"><p>Values and beliefs</p></td><td align="left"><p>2</p></td><td align="left"><p>3%</p></td></tr><tr><td align="left"><p>Total</p></td><td align="left"><p>85</p></td><td align="left"><p>100%</p></td></tr></tbody></table> </ephtml> </p> <p>Design judgments involve the deliberate choices practitioners make to balance conflicting priorities and constraints (Nelson & Stolterman, [<reflink idref="bib29" id="ref31">29</reflink>]). These judgments are often shaped by the designer's expertise, contextual understanding, and the availability of resources (Lachheb & Boling, [<reflink idref="bib26" id="ref32">26</reflink>]). Zhu et al. ([<reflink idref="bib47" id="ref33">47</reflink>]) explored how novice instructional designers navigate design judgments, revealing that limited experience often leads to reliance on prescriptive models and tools. Experienced designers exhibit more nuanced decision-making, leveraging heuristics and creative problem-solving to address unique design challenges (Demiral, [<reflink idref="bib8" id="ref34">8</reflink>]; Demiral-Uzan & Boling, [<reflink idref="bib9" id="ref35">9</reflink>]; Honebein, [<reflink idref="bib10" id="ref36">10</reflink>]). This underscores the importance of cultivating both foundational knowledge and adaptive expertise in instructional design education.</p> <p>In instructional design, design judgments are intricately linked to decision-making as they require weighing multiple factors such as learner needs, content complexity, and technological affordances (Demiral-Uzan & Boling, [<reflink idref="bib9" id="ref37">9</reflink>]). Yilmaz and Cagiltay ([<reflink idref="bib44" id="ref38">44</reflink>]) emphasize that instructional designers must balance pedagogical goals with technological possibilities, often making trade-offs to meet project deadlines or budget constraints. Such decisions are inherently complex and require critical thinking, reflective practice, and a robust understanding of instructional theories. Further research could explore how designers make these judgments in dynamic and resource-constrained environments, contributing to the development of more effective decision-making frameworks and tools.</p> <p>Pedagogical decision-making focuses on instructional choices that directly impact teaching and learning strategies. These decisions often involve selecting appropriate methodologies, scaffolding learning, and aligning instructional goals with learner needs. Ateh ([<reflink idref="bib2" id="ref39">2</reflink>]) highlights how science teachers' elicitation practices influence formative assessment design, demonstrating the interplay between pedagogical knowledge and practical decision-making. Xu et al. ([<reflink idref="bib43" id="ref40">43</reflink>]) discuss how pre-service teachers grapple with aligning technology integration to pedagogical objectives, showcasing the challenges of applying theoretical knowledge in practice.</p> <p>Pedagogical decision-making requires a deep understanding of both content and context. This process often intersects with design judgments, as designers must decide how to best facilitate learning while addressing learner needs and constraints (Stefaniak et al., [<reflink idref="bib35" id="ref41">35</reflink>]). Research exploring how instructional designers navigate pedagogical complexities could inform the development of more effective training programs for instructional designers.</p> <p>Decision-making strategies encompass the systematic approaches instructional designers use to evaluate options, prioritize actions, and resolve conflicts. Stefaniak et al. ([<reflink idref="bib34" id="ref42">34</reflink>]) found that conjecture strategies are common among instructional design students, enabling them to anticipate and address potential challenges. Such strategies are critical for navigating the complexities of instructional design projects, where decisions often involve balancing competing demands and limited resources.</p> <p>In practice, decision-making strategies are closely tied to the iterative nature of instructional design. Designers frequently revisit and revise their choices as new information emerges or as project goals evolve. Lachheb and Boling ([<reflink idref="bib26" id="ref43">26</reflink>]) argue that decision-making strategies are not static but are shaped by the designer's experience and the specific context of the project. By studying how these strategies are developed and refined, instructional design education can better equip practitioners with the tools and frameworks necessary for effective decision-making.</p> <p>Technology integration and adaptation involves making informed decisions about incorporating and customizing technological tools to enhance learning experiences. Baek et al. ([<reflink idref="bib3" id="ref44">3</reflink>]) investigated factors influencing teachers' use of technology, highlighting the importance of perceived ease of use and alignment with pedagogical goals. Xu et al. ([<reflink idref="bib43" id="ref45">43</reflink>]) explored how pre-service teachers make decisions about technology integration, emphasizing the role of contextual factors such as institutional support and learner preferences.</p> <p>For instructional designers, technology integration requires a nuanced understanding of both the potential and limitations of available tools. Effective decision-making in this domain involves evaluating the pedagogical implications of technology choices, ensuring they align with instructional objectives and learner needs (Boer and Asino, [<reflink idref="bib5" id="ref46">5</reflink>]; Hsu et al., [<reflink idref="bib18" id="ref47">18</reflink>]). As technological advancements continue to evolve, research into adaptive strategies for technology integration can provide valuable insights for instructional design practice, particularly in addressing equity and accessibility challenges.</p> <p>Reflective practice is a critical component of decision-making in instructional design, enabling practitioners to critically evaluate their choices and consider their impact on learning outcomes (Blackwell & Pepper, [<reflink idref="bib4" id="ref48">4</reflink>]; Ge & Hardré, [<reflink idref="bib14" id="ref49">14</reflink>]; Kenny et al., [<reflink idref="bib21" id="ref50">21</reflink>]). Enderle et al. ([<reflink idref="bib11" id="ref51">11</reflink>]) highlight how reflective practices during the co-design process led to changes in teachers' beliefs and instructional strategies, underscoring the transformative potential of reflective decision-making. Wolfe et al. ([<reflink idref="bib42" id="ref52">42</reflink>]) emphasize the importance of reflection in training pre-service practitioners to make data-driven instructional decisions.</p> <p>Reflective practice fosters continuous improvement by encouraging designers to analyze their decisions and identify areas for growth. This iterative process not only enhances decision-making skills but also supports the development of a deeper understanding of instructional deign practices (McDonald, [<reflink idref="bib27" id="ref53">27</reflink>]). Integrating reflective practice into instructional design education can empower designers to navigate complex challenges with confidence, making it a vital area for further research and professional development.</p> <hd id="AN0187262891-13">Discussion</hd> <p>Decision-making in instructional design contexts has increasingly become a popular research topic across the decades from 1990 to 2023. It is not surprising because scholars and practitioners have gradually acknowledged the role of instructional design decision-making as an ill-structured, dynamic, and situated process within a design space affected by a wide range of contextual factors and the affordances of the environment (Boling & Smith, [<reflink idref="bib7" id="ref54">7</reflink>]; Stefaniak et al., [<reflink idref="bib35" id="ref55">35</reflink>]; Webb & Cox, [<reflink idref="bib39" id="ref56">39</reflink>]). This scoping review indicated that researchers have been interested in identifying (<reflink idref="bib1" id="ref57">1</reflink>) decision-making products for instructional design in multiple contexts, (<reflink idref="bib2" id="ref58">2</reflink>) relevant contextual factors that affect instructional design decisions, and (<reflink idref="bib3" id="ref59">3</reflink>) strategies to facilitate instructional design decision-making in practitioners. These finding suggests that more research is needed to identify not only decision-making products, i.e., how practitioners leverage different factors and their reasoning to make decisions, but also decision-making processes, i.e., why practitioners prioritize certain factors within their design decision-making processes.</p> <p>This review identified that researchers have perceived instructional design decision-making from multiple perspectives; however, limited empirical evidence has been found that explicitly described what role pedagogical reasoning processes in practitioners played within their design decision-making processes. It is possibly because it is difficult and arbitrary to dissect and examine practitioners' instructional design decision-making processes in different contexts.</p> <p>Meanwhile, this study identified that researchers have been aware of the importance of decision-making in instructional design since 2006. The majority of empirical studies for instructional design decision-making were conducted in the most recent decade. Most empirical studies about instructional design decision-making in higher educational contexts acknowledged the role of instructional design judgments in instructional design contexts. It implied that instructional designers and researchers in higher educational settings were more conscious of the critical role of instructional design judgments and its influences in design decision-making (Lachheb & Boling, [<reflink idref="bib26" id="ref60">26</reflink>]). On the contrary, the empirical studies in K-12 settings were more focused on the content-based learning and professional development strategies for instructional design decision-making. It suggested that K-12 educators and researchers emphasized more on the professional strategies and practices that supported teachers' decision-making in accordance with their contexts, rather than how and why teachers made design decisions for their students based on their reasoning processes in their instructional design contexts.</p> <hd id="AN0187262891-14">Implications for Instructional Designers</hd> <p>The findings of this review underscore the importance of decision-making as a core competency in instructional design. Instructional design courses must evolve to provide explicit training in decision-making strategies, equipping future designers with the tools and frameworks necessary to navigate complex, real-world challenges (Stefaniak et al., [<reflink idref="bib35" id="ref61">35</reflink>]). Instructional design programs should incorporate reflective practice as a foundational component, enabling students to critically evaluate their design choices and their impact on learning (McDonald, [<reflink idref="bib27" id="ref62">27</reflink>]). This can be achieved through structured activities like design journals, peer feedback, and iterative design projects that require reflection and adaptation.</p> <p>Furthermore, integrating decision-making tools into instructional design education can enhance students' ability to make informed and contextually appropriate choices (Lachheb and Boling, [<reflink idref="bib26" id="ref63">26</reflink>]). Training on tools such as decision matrices, learner analytics platforms, and scenario-based simulations can help students practice applying theoretical knowledge to practical situations. These tools should not only support decision-making efficiency but also encourage reflective evaluation of the outcomes, fostering a habit of continuous improvement.</p> <p>The implications extend to the broader ecosystem of instructional design research and practice. Stakeholders, including policymakers, administrators, and developers of educational technology, must recognize the critical role of decision-making in effective instructional design. By emphasizing decision-making as a key area for research and education, the field can better prepare designers to support learning in a variety of contexts.</p> <hd id="AN0187262891-15">Future Research</hd> <p>The studies analyzed in this scoping review emphasize significant progress in understanding decision-making processes in instructional design; however, critical gaps remain. Future research should prioritize examining how novice and expert instructional designers develop, refine, and implement decision-making strategies across different educational contexts. Specifically, there is a need to explore the cognitive and reflective practices involved in balancing competing priorities, such as aligning with instructional goals, addressing learner diversity, and optimizing technological affordances. Additionally, longitudinal studies could provide valuable insights into how instructional designers' decision-making evolves with experience and exposure to varied design challenges.</p> <p>Another critical area for future inquiry involves the development and evaluation of tools and frameworks to support decision-making in instructional design. Studies could investigate the efficacy of tools like design rubrics, heuristics, and analytics dashboards in enhancing decision-making efficiency and effectiveness. Research could examine how these tools foster reflective practice, helping designers assess the implications of their choices on learning outcomes and equity. This line of research could also explore the potential of AI-driven tools to provide real-time feedback and adaptive support for decision-making during the instructional design process.</p> <p>Finally, there is a more pressing need for research into how instructional design courses and professional development programs can better prepare practitioners for complex decision-making. Future studies might assess the integration of case-based learning, simulations, and collaborative design tasks into instructional design curricula to promote the acquisition of practical decision-making skills. More research is needed to better understand how reflective practice is taught and reinforced in these contexts, ensuring that instructional designers develop the capacity for thoughtful, evidence-based, and adaptive decision-making.</p> <hd id="AN0187262891-16">Declarations</hd> <p></p> <hd id="AN0187262891-17">Conflict of Interest</hd> <p>The authors declare that they have no conflict of interest.</p> <hd id="AN0187262891-18">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0187262891-19"> <title> References </title> <blist> <bibl id="bib1" idref="ref25" type="bt">1</bibl> <bibtext> Arksey H, O'Malley L. Scoping studies: Towards a methodological framework. International Journal of Social Research Methodology. 2005; 8; 1: 19-32. 10.1080/1364557032000119616</bibtext> </blist> <blist> <bibl id="bib2" idref="ref39" type="bt">2</bibl> <bibtext> Ateh, C. M. (2015). 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  Data: A Scoping Review to Explore How Decision-Making Is Discussed in the Field of Learning Design
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  Data: <searchLink fieldCode="AR" term="%22Jill+Stefaniak%22">Jill Stefaniak</searchLink> (ORCID <externalLink term="http://orcid.org/0000-0002-9571-9215">0000-0002-9571-9215</externalLink>)<br /><searchLink fieldCode="AR" term="%22Meimei+Xu%22">Meimei Xu</searchLink><br /><searchLink fieldCode="AR" term="%22Fan+Yang%22">Fan Yang</searchLink>
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  Data: <searchLink fieldCode="DE" term="%22Instructional+Design%22">Instructional Design</searchLink><br /><searchLink fieldCode="DE" term="%22Decision+Making%22">Decision Making</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Technology%22">Educational Technology</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+History%22">Educational History</searchLink><br /><searchLink fieldCode="DE" term="%22Professional+Development%22">Professional Development</searchLink><br /><searchLink fieldCode="DE" term="%22Educational+Research%22">Educational Research</searchLink>
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  Data: 10.1007/s11528-025-01053-5
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  Data: Instructional design practices consist of design decisions. It often comprises decisions across analysis, design, development, implementation, and evaluation. This paper presents the findings of a scoping review that explored how decision-making is discussed in learning design research over the past four decades. This scoping review of research investigates conceptual papers and empirical studies that discussed decision-making in instructional design and/or educational technology contexts. The sample covers research published over four decades (1990-2023). By gaining an understanding of how decision-making is investigated and discussed in different contexts of educational technology, the field is positioned to support designers in the field as well as throughout their professional development.
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      – SubjectFull: Instructional Design
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      – SubjectFull: Decision Making
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      – TitleFull: A Scoping Review to Explore How Decision-Making Is Discussed in the Field of Learning Design
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      – BibEntity:
          Dates:
            – D: 01
              M: 07
              Type: published
              Y: 2025
          Identifiers:
            – Type: issn-print
              Value: 8756-3894
            – Type: issn-electronic
              Value: 1559-7075
          Numbering:
            – Type: volume
              Value: 69
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: TechTrends: Linking Research and Practice to Improve Learning
              Type: main
ResultId 1