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A Multilevel Evaluation Model for Active Physical Learning Environments: A Comparative Study of the Phillips, Reeve, and McCloskey Models
Marzieh Aslani, Mohammadali Khanmohammadi, Mahdi Hamzenejad, Mahmoud Talkhabi, Farhang Mozafar,
Volume 14, Issue 1 (4-2026)
Abstract
The physical learning environment plays a critical role in shaping the quality of students’ learning experiences, particularly through its interaction with motivational and cognitive processes. Despite their foundational significance in explaining various dimensions of learning, the two prominent theoretical models—Reeve’s Student Engagement model and McCloskey’s Executive Functions model—have rarely been explicitly utilized in the design and analysis of physical learning environments. Furthermore, a comparative exploration of their complementary and integrative analytical potentials, particularly in the context of the physical environment, represents a notable research gap. Addressing this gap holds promise for enhancing both the theoretical foundation and practical strategies in the design of learning spaces. Therefore, this article aims to examine the potential of Reeve’s motivational model and McCloskey’s executive function model for analyzing the physical learning environment. By focusing on learners’ internal processes—namely, types of engagement in the former and executive functions in the latter—these two models offer a framework in which the physical environment is not seen as a neutral backdrop, but rather as an active factor in shaping learning experiences. The central research questions are: What dimensions and indicators does each model propose for analyzing the physical environment in relation to student learning? What are the contributions of a comparative analysis of these two models to understanding and analyzing the physical learning environment? Accordingly, this study employs a comparative analysis with a qualitative approach, using documentary and library research as the data collection method. To this end, the two selected theoretical models—Reeve’s model, which focuses on motivation and types of student engagement, and McCloskey’s model, which emphasizes cognitive executive functions—were first examined in terms of their foundational concepts, internal structure, and applications in learning environments. Subsequently, through conceptual content analysis and deductive inference, the potential of each model to analyze various dimensions of the physical learning environment—including spatial organization, functional uses, physical elements, and formal properties—was investigated and compared. The aim of this comparison was to identify the distinguishing and overlapping features of the two models in analyzing the physical learning environment and to clarify their roles in explaining the characteristics of effective physical environments for learning. Reeve’s model, grounded in Self-Determination Theory, emphasizes the teacher’s role in supporting students’ autonomy and fostering behavioral, emotional, cognitive, and agentic engagement. In contrast, McCloskey’s model focuses on brain-mind executive functions structured into clusters and performance arenas, offering a neuropsychological perspective on the learner’s interaction with the environment. A comparative study of Reeve’s psychological model and McCloskey’s neuropsychological model reveals that each framework, grounded in distinct theoretical foundations, addresses complementary aspects of the relationship between physical environment and learning. The dimensions and indicators of the two models can be analyzed from two perspectives. At the conceptual dimention, Reeve’s model focuses on intrinsic motivation driven by psychological needs (autonomy, competence, relatedness) and the multiple dimensions of engagement (cognitive, emotional, behavioral, and agentic). In contrast, McCloskey’s model emphasizes the neurocognitive processes underlying learning by proposing clusters of executive functions (Attending, Engaging, Monitoring and Adjusting, Performing Efficiently, Managing Memory, Inquiring Reflectively, and Problem Solving), along with four contextual arenas in which these functions operate (intrapersonal, interpersonal, environmental, and symbolic systems). At the methodological dimention, Reeve’s model is applicable in studies of the physical environment that focus on measuring motivation and observing types of engagement. Meanwhile, McCloskey’s framework is suitable for evaluating the physical environment from precise cognitive perspectives, analyzing mental functions, and designing interventions based on cognitive neuroscience. These methodological differences are reflected in the types of assessment tools, levels of analysis, and nature of data employed. At the practical dimention, Reeve’s model, with its focus on intrinsic motivation, psychological needs, and multifaceted engagement, provides a rich conceptual framework for analyzing the physical environment from a motivational-social perspective. McCloskey’s  model, on the other hand, offers an analytical basis for assessing the physical environment in terms of its support or hindrance of neurocognitive functioning based on executive operations. Ultimately, both models enable the analysis of physical learning environments in terms of their alignment with motivational and executive mental needs and support for self-regulatory processes. Accordingly, Reeve’s model is particularly useful in analyzing and designing learning spaces that emphasize motivation, choice, interaction, and learner-centeredness. It is especially applicable to the design of motivational spaces that promote positive emotions and active engagement, offering flexibility, personalization, and suitability for small, medium, and large group activities. Conversely, McCloskey’s model Is effective in analyzing environments that require minimized distractions, enhanced concentration, spatial order, and quick feedback. It emphasizes efficient spatial organization, visual clarity, and the design of personal and group spaces aligned with cognitive goals such as inquiry and problem-solving. In conclusion, these two models are not in conflict but are analytically complementary. Their integration offers a synergistic perspective on the motivational and cognitive dimensions of the physical learning environment. Combining insights from both models allows for a deeper, multilayered, and more integrated analysis of the relationship between physical space and learning. Such an approach offers educational space designers, educational psychologists, and learning researchers a comprehensive framework for designing environments that support both learner motivation and cognitive functioning.
 

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