Introduction
Urban planning, as an interdisciplinary and complex field, is the synthesis of multiple disciplines that enables the understanding and analysis of multifaceted urban phenomena. Within this context, "Urban Geography" serves as a fundamental course in the undergraduate urban planning curriculum, playing a key and undeniable role in shaping the theoretical and analytical foundations of students. The intrinsic nature of this course requires effective and deep learning, necessitating the confrontation, processing, and analysis of a vast volume of diverse data, including statistics, maps, images, charts, and dense theoretical texts. However, existing evidence suggests that conventional teaching methods in this field, which rely mainly on the traditional teacher-centered model and one-way transmission of information, face serious and fundamental challenges in creating an active and dynamic learning environment for managing and analyzing this volume of data.
The main problem addressed in this research is the lack of a codified and efficient educational model that can facilitate the process of collecting, organizing, analyzing, and integrating information for students. In the current educational system, students often face scattered resources, unstructured course notes, and a massive volume of digital files. Managing this disorganized information itself becomes a cognitive challenge, leading to increased "extraneous cognitive load" and reduced learning capacity. This informational chaos can lead to superficial learning, reduced academic motivation, and an inability to establish links between abstract theoretical foundations and real-world instances in the urban space.
Conversely, modern learning theories, particularly Constructivism, emphasize that learning is an active and internal process wherein the learner must reconstruct knowledge through interaction with the environment and information. Furthermore, Cognitive Load Theory asserts that if an educational task imposes excessive cognitive load on the student's mind, the learning process is disrupted. Therefore, there is an increasing need for tools that allow students to organize, categorize, and link information in a meaningful way. In the digital age, database management and personal knowledge management software hold immense potential to achieve this goal, yet their use in the Iranian academic sphere, especially in design-oriented disciplines, remains limited and lacks a specific pedagogical framework. Recognizing this gap, this research focuses on using "Fishnegar" software as an offline educational database to present a novel teaching model.
The Purpose of the Research
The primary objective of this research is to propose, formulate, and validate a novel teaching method based on an offline educational database using "Fishnegar" software. This study aims to assess the effectiveness of this method on key learning components, including academic achievement, motivation, and analytical skills of urban planning students. Essentially, this research seeks not only to answer the question "Does this method work?" (quantitative dimension) but also to explicate "How and why does this method work?" and what its fundamental principles are (qualitative dimension). The research questions are designed in two areas: In the qualitative domain, the study seeks to identify the characteristics, principles, and foundations of designing and implementing this teaching method, as well as its advantages and challenges from the perspective of professors and students . In the quantitative domain, the research aims to test the hypothesis of whether using the offline educational database teaching method has a significant effect on increasing academic achievement, motivation, and students' information organization and analysis skills. The ultimate goal is to develop a model that goes beyond mere information transfer and strengthens "learning how to learn" and "knowledge management" skills in students.
Methodology
This research is based on a "Mixed Methods Strategy," specifically utilizing an "Exploratory Sequential Design" (QUAL → quan). This approach was chosen because, before testing the effectiveness of the teaching method, it was necessary to first identify its dimensions and principles through qualitative exploration.
In the First Phase (Qualitative), the goal was to explore and formulate the principles of the teaching method. The population included experienced urban planning professors and undergraduate students. Purposeful sampling was used to select 10 professors and 15 students. Data collection tools included in-depth semi-structured interviews and two focus group sessions. The resulting data were coded and analyzed using Thematic Analysis (Braun & Clarke's six-step method) to extract main themes and principles.
In the Second Phase (Quantitative), the research design was "Quasi-experimental with Pre-test/Post-test and Non-equivalent Control Group". The statistical population consisted of students in the Urban Geography course, from which two classes were selected via convenience sampling: one class as the experimental group (30 students) trained with the new method based on "Fishnegar," and another class as the control group (32 students) taught via the traditional lecture-based method. The educational intervention lasted for 16 weeks. Assessment tools included a researcher-made academic achievement test (validated with a reliability of 0.81), a standard academic motivation questionnaire, and an observational checklist for analytical skills . Quantitative data were analyzed using descriptive statistics and One-Way Analysis of Variance (ANOVA) in SPSS software to examine significant differences between the two groups. Statistical assumptions such as normality tests and Levene's test for equality of variances were also checked and confirmed.
Findings and Discussion
Qualitative Findings: The qualitative data analysis led to the identification and formulation of five fundamental principles that constitute the framework of the proposed teaching method. These principles are:
1. Structured Organization of Information: Transitioning from the accumulation of scattered information to a coherent network structure that reduces cognitive load.
2. Facilitating Self-Directed Learning: Changing the student's role from a passive recipient to an active participant and "knowledge architect" who takes responsibility for their own learning.
3. Linking Theory and Practice: Permanently connecting abstract concepts and theories to real-world instances and maps to achieve situated learning.
4. Enhancing Critical Thinking: Moving from memory-based learning toward analysis, comparison, and evaluation of information using the database structure.
5. Increasing Interaction and Shared Knowledge: Using individual achievements in the database as a basis for group discussions and social learning.
Quantitative Findings: The quantitative results indicated the extraordinary effectiveness of the new teaching method. In the pre-test, there was no significant difference between the mean scores of the experimental group (49.90) and the control group (51.16), indicating initial homogeneity between the two groups. However, in the post-test, the results were vastly different. The total mean score of the experimental group reached 79.58, whereas the control group scored a mean of 52.55. This 27-point difference demonstrates a deep educational gap created by the intervention. The ANOVA test results, with an F-value of 273.55 and a significance level of p < 0.001, showed this difference to be statistically highly significant. More importantly, the effect size (Eta-squared) was calculated at 0.82, indicating that 82% of the variance in academic achievement was attributable to the new teaching method. Furthermore, in the descriptive questions section measuring higher cognitive levels (analysis and evaluation), the experimental group showed a remarkable improvement of 12.1 points, while the control group experienced a performance decline.
Discussion and Integration: The quantitative findings are explained by the qualitative principles. The dramatic increase in scores resulted from the reduction of "extraneous cognitive load" due to the structured organization of information in the software. Instead of expending energy searching for scattered resources, students focused on analyzing and understanding relationships (germane cognitive load). Additionally, the increase in motivation observed in the experimental group can be explained by the principle of "self-directed learning" and the satisfaction of needs for autonomy and competence. The students' high ability to answer analytical questions was a direct result of classroom exercises linking theory to practice and building semantic networks within the database. In essence, this teaching method, by simulating the thinking process of a researcher, cultivated higher-order cognitive skills in students.
Conclusion
This research provides strong empirical and theoretical evidence confirming the efficiency and effectiveness of the "Offline Educational Database-Based Teaching Method" using "Fishnegar" software for the Urban Geography course. The results demonstrated that this approach can overcome the major challenges of traditional urban planning education, including informational chaos, student passivity, and the gap between theory and practice. The five principles formulated in this research (Structured Organization, Self-Direction, Theory-Practice Link, Critical Thinking, and Interaction) offer a practical and reliable framework for professors and instructional designers to deliver theoretical and practical courses with higher quality.
By empowering students with knowledge management tools, this method prepares them for lifelong learning. The practical implications of this research include the necessity of revising urban planning curricula to include information management skills and changing the role of professors from knowledge transmitters to learning facilitators. Although this research faced limitations such as sample size and the potential Hawthorne effect, its results are robust enough to promise a transformation in higher education for urban planning. It is suggested that future research test this model in other courses, universities, and through longitudinal studies.