Based on the research topic, the following are potential questions that could be explored:
1. What is the current level of climate knowledge among architecture students, and how do they perceive the importance of climate knowledge in their profession?
2. What role do self-learning strategies play in their learning process?
3. What are the key factors influencing the development of climate knowledge among architecture students, and how can these factors be leveraged to support their learning?
4. Can self-learning strategies, such as online courses, workshops, or peer-to-peer learning, effectively improve climate knowledge among architecture students?
5. What are the perceived challenges that architecture students face in developing their climate knowledge?
6. What are the implications of climate knowledge on the design and construction of sustainable buildings, and how can architecture students be prepared to address these implications through self-learning and other methods?
These research questions can serve as a starting point for achieving the research goal of understanding the role of self-learning in supporting climate knowledge among architecture students.
Research Objectives:
The primary goal of the research is to assess the extent to which architecture students practice self-learning skills to establish an organized framework in teaching sustainable architectural design that preserves the climate. This involves considering individual differences among learners, such as variations in abilities, inclinations, experiences, and learning speeds. This main goal is supported by the following sub-objectives:
• Identify the self-learning techniques necessary for architecture students in light of sustainability requirements.
• Determine the extent to which architecture students practice self-learning techniques.
• Reveal differences in the level of practice of self-learning techniques based on academic level.
The importance of the current study lies in the significance of self-learning as a method that contributes to finding solutions to many environmental and societal problems. The study's importance can be defined by providing feedback to those responsible for architectural education programs about the extent to which architecture students possess self-learning skills, aiming to enhance strengths and address weaknesses. Additionally, it reveals some behavioral aspects of self-learning skills and encourages students to practice them.
In the current research, addressing certain points can help answer the research questions and achieve its primary objective by using a mixed-methods approach to combine quantitative and qualitative data. This approach focuses on a specific context or group—namely, the students—to provide more accurate insights and a comprehensive understanding of the relationship between climate knowledge, self-learning, and design. It also contributes to developing more effective strategies for enhancing climate knowledge and sustainability.
1- Self-Learning Methods in Design
• Self-Learning
Self-learning, in its cognitive framework, extends to be practiced by individuals outside educational institutions through independent work, primarily via self-study in various fields of science, art, literature, and others. It can be described as a process where individuals take the initiative, with or without the help of others, to identify their educational needs, set their goals, determine their learning sources, and select appropriate educational techniques for implementation (Palio, 2010).
Therefore, it is essential to distinguish between self-learning skills and self-learning techniques.
• Self-Learning Skills:
- Vision and Imagination: This includes forming visions and using them to generate new solutions and creative ideas.
- Critical Thinking and Judgment: This involves expressing opinions, making judgments, making decisions, critiquing ideas, and determining which ideas can be implemented.
- Purposeful Culture: This involves instilling various forms of culture and analyzing the meanings of symbols and cultural forms.
- Collaboration, Teamwork, and Community Service: This is related to engagement with cultural centers and community institutions.
- Adaptability, Change, and Acquiring New Skills: This includes the ability to adapt, embrace change, and acquire new capabilities and skills (Badawi, 2009).
In the context of what the labor market expects from the workforce in the knowledge economy era, self-learning skills include the ability to acquire information and transform it into usable knowledge, the capacity to adapt and learn quickly, proficiency in computer technology and its applications, the ability to collaborate and work within a team, mastery of verbal and written communication skills, proficiency in multiple languages, the ability to move and adapt swiftly, and an awareness of the necessity to monitor and keep up with changes (Beruvides, 2018).
• Self-Learning Techniques:
1) Programmed Self-Learning: This involves independent learning without teacher assistance, where the student acquires knowledge, skills, attitudes, and values specified by the program using learning media and techniques. This includes printed educational materials or computer-programmed content (Safapour, 2019).
2) Modular Units: In this method, the student starts by identifying the topics they wish to learn. They then follow steps guided by the teacher, such as undergoing pre-assessment, engaging with the module, and subsequently participating in post-assessment and self-assessment (Bacomo, 2022).
3) Educational Packages (Kits): The concept of educational packages is similar to that of instructional modules in form and method, but they are broader and more comprehensive. Educational packages are one of the most important self-learning methods, as they shift the focus from the teacher and the curriculum to the student themselves. The educational material is presented to learners in a way that matches their readiness, abilities, and personal characteristics (Raghuveer, 2012).
4) Electronic Teaching: This method aims to teach certain information and skills to students by conducting competitions between learners or between the learner and the program through educational games designed to develop problem-solving abilities.
5) Simulation: An educational method used by instructors to bring concepts closer to students. This technique aims to create real-life scenarios that closely resemble actual situations, allowing students to learn through tangible experiences.
6) Training and Practice: In this method, the educational program is designed to support traditional classroom approaches. Training programs and practice sessions make the subject matter familiar to students and help develop the automatic recall of information (Beruvides, 2018).
7) Computer-Assisted Teaching (Multimedia): With the advent of high-capacity storage media such as video discs and compact discs, multimedia teaching using computers has become possible. This method presents information to students through a combination of written texts, still and animated images, audio, and colors.
8) Mastery Learning: This approach involves providing learners with well-organized instructional units with predetermined objectives. Learners are not allowed to progress from one unit to the next until they achieve the required level of mastery. If a learner does not reach the desired level, remedial materials are provided to help them achieve the objectives (Abdelhamid, 2022).
Recent technological advancements and their use in the educational field have led to the emergence of several modern educational systems, particularly those focused on self-learning. These systems integrate curricula and learning patterns with the outcomes of these technological developments (Jamel, 2000).
Architectural design has unique characteristics in terms of content and teaching methods. In most universities, architectural design is still taught based on the instructor’s and supervisor’s personality and their proficiency in the profession. While this approach provides students with practical experiences, it also molds them into a framework of dependency, which can lead to superficial imitation without a deep understanding of the true meaning of design.
Practical Study
The current study employs a descriptive methodology to analyze self-learning skills among architecture students in several Arab countries. It is based on a random sample of students from countries experiencing political, economic, and social crises, which provides a realistic perspective on the challenges these students face in developing their self-learning skills.
• Strengths of the Study:
1. Geographical Diversity: The study includes a sample of students from Syria, Egypt, Yemen, and Iraq, which enhances the reliability of the results and reflects real challenges in different educational environments.
2. Robust Questionnaire: The questionnaire was developed based on an in-depth literature review of self-learning skills and is systematically divided into five dimensions that cover various important aspects of architectural design learning.
3. Credibility of Results: The study utilized Cronbach's alpha coefficient to ensure the reliability and internal consistency of the questionnaire, which enhances the trustworthiness of the results obtained.
4. Statistical Analysis: The study employed means, standard deviations, and percentages, along with the T-Test, to examine differences between academic years, demonstrating the depth of analysis and the use of advanced statistical tools.
• Limitations and Challenges:
1. Temporal Diversity: There were no time differences in data collection between the various countries, which could affect the results given the rapid political and social changes.
2. Sample of the Study: The sample included students from multiple countries, with a total of 150 students:
- 85 students from Syria (60 students from the third year, 25 students from the fifth year)
- 65 students from other Arab countries, including Egypt, Yemen, and Iraq (40 students from the third year, 25 students from the fifth year)
3. Selection of Students from Different Academic Years: Choosing students from different academic years may reflect significant changes in acquired skills and knowledge, which could help in assessing the impact of academic progression on skill development.
4. Sample Limited to Specific Academic Years: The sample was restricted to students in their third year (a critical foundational stage) and fifth year (graduating students), which may provide a comprehensive view of the development of self-learning skills during crucial stages of architectural education.
5. The study selected a random sample of architecture students from the third and fifth years from Syria and various Arab universities in Egypt, Yemen, and Iraq.
6. Studied Skills: The study focused on self-learning skills as defined by the researcher and included in the study tool.
• Study Methodology and Procedures
The study employed a descriptive methodology aimed at depicting the current situation through data collection, classification, interpretation, and discussion.
The study population consisted of two random groups of architecture students:
- Group One: 85 students from Syria.
- Group Two: 65 students from Arab countries (Egypt, Yemen, Iraq).
Table 1. Distribution of sample members by year and country:
|
Total
|
Arab countries
|
Syria
|
Academic year
|
|
100
|
40
|
60
|
Third
|
|
50
|
25
|
25
|
Fifth
|
|
150
|
85
|
85
|
Total
|
• Study Tool
The study employed an electronic questionnaire (distributed via specialized social media platforms) aimed at architecture students to measure their engagement with self-learning skills. The questionnaire was developed based on educational literature related to self-learning and its various skills.
• Questionnaire Dimensions:
1. Dimension One: Reading and Continuous Thinking: Measures aspects of self-directed reading and students' utilization of knowledge sources.
2. Dimension Two: Structured Self-Learning: Assesses students' use of the internet and computerized programs to enhance their design capabilities.
3. Dimension Three: Communication and Interaction: Measures the extent of collaboration and group learning among students.
4. Dimension Four: Experiences and Imagination: Assesses students' use of life experiences and imagination in developing design skills.
5. Dimension Five: Problem Solving and Adaptability: Evaluates students' ability to solve problems and make decisions in light of social and economic changes.
• Questionnaire Reliability
The reliability of the questionnaire was calculated using the Cronbach's alpha coefficient, and the results were as follows:
Table 2. Cronbach's alpha values
|
Alpha value
|
Questionnaire axis
|
|
0.823
|
Continuous reading and thinking
|
|
0.798
|
Self-organized learning
|
|
0.896
|
Communication and communication
|
|
0.801
|
Experiences and imagination
|
|
0.901
|
Problem solving
|
|
0.921
|
Questionnaire in general
|
• Internal Consistency of the Questionnaire
Internal consistency was calculated using the correlation coefficient between each item of the questionnaire and the dimension to which it belongs:
Table 3. Internal consistency by correlation coefficient
|
Statistical Significance
|
Correlation Coefficient
|
Questionnaire axis
|
|
0.01
|
0.746
|
Continuous reading and thinking
|
|
0.01
|
0.596
|
Self-organized learning
|
|
0.01
|
0.735
|
Communication and communication
|
|
0.01
|
0.658
|
Experiences and imagination
|
|
0.01
|
0.898
|
Problem solving
|
|
0.01
|
0.921
|
Questionnaire in general
|
• Questionnaire Scoring Criteria
Table 4. The response scores were distributed across five categories
|
Percentage Range
|
Score Range
|
Category
|
|
20%-35.9%
|
1-1.79
|
Very Low
|
|
36%-51.9%
|
1.8-2.59
|
Low
|
|
52%-67.9%
|
2.6-3.39
|
Moderate
|
|
68%-83.9%
|
3.4-4.19
|
High
|
|
84%-100%
|
4.2-5
|
Very High
|
Study Results
The study revealed that architecture students engage in self-learning significantly, particularly in the areas of problem-solving and decision-making.
Table 5. Summary of Results by Dimensions
|
Dimension
|
Percentage
|
|
Problem Solving and Adaptability
|
82.454%
|
|
Structured Self-Learning
|
80.518%
|
|
Experiences and Imagination
|
78.617%
|
|
Communication and Interaction
|
77.621%
|
|
Reading and Continuous Thinking
|
74.959%
|
|
Overall Mean
|
78.533%
|
The study revealed that the majority of architecture students (82.45%) possess strong problem-solving and adaptability skills, indicating their ability to tackle complex challenges and adjust to new situations. Additionally, the study found that 80.52% of architecture students engage in self-directed learning, suggesting that they are capable of effectively planning and managing their own learning processes.
The results indicate that 78.62% of architecture students value experiential learning and imagination, highlighting the significance of practical experience and creative expression in their learning process. The study also shows that 77.62% of architecture students prioritize communication and collaboration, emphasizing the need for effective teamwork and interpersonal skills in their profession.
Additionally, 74.96% of architecture students engage in continuous learning and critical thinking, reflecting their commitment to ongoing professional development and intellectual curiosity. Thus, the overall mean score of 78.53% suggests a strong emphasis on self-directed learning, problem-solving, and experiential learning among architecture students.
These findings can be used to inform teaching practices, curriculum development, and student support services in architecture programs. For instance, educators can design instructional activities that promote self-directed learning, problem-solving, and experiential learning, while also providing opportunities for students to develop their communication and collaboration skills.
• Differences by Academic Level
The study revealed statistically significant differences between third-year and fifth-year architecture students in their practice of self-directed learning skills.
Table 6. Results of the T-Test for the significance of differences in acquiring self-directed learning skills in light of the level variable (Third Year – Fourth Year)
|
Statistical Significance
|
t-value
|
Standard Deviation
|
Mean
|
N
|
Group
|
Questionnaire axis
|
|
Significant at 0.01
|
3.837
|
2.93681
|
33.0526
|
100
|
Third Year
|
Skill of Continuous Inquiry and Thinking
|
|
2.73242
|
34.9259
|
50
|
Fifth Year
|
|
|
Significant at 0.01
|
3.303
|
2.83823
|
27.6632
|
100
|
Third Year
|
Skill of Self-Regulated Learning
|
|
1.89606
|
29.0926
|
50
|
Fifth Year
|
|
|
Significant at 0.01
|
3.236
|
4.09153
|
41.9368
|
100
|
Third Year
|
Skill of Communication and Collaboration (Group Learning)
|
|
3.13526
|
44.0185
|
50
|
Fifth Year
|
|
|
Significant at 0.01
|
3.401
|
3.58571
|
38.6105
|
100
|
Third Year
|
Skill of Experience and Imagination
|
|
2.79968
|
40.5370
|
50
|
Fifth Year
|
|
|
Significant at 0.01
|
2.789
|
3.28364
|
28.3474
|
100
|
Third Year
|
Skill of Problem Solving and Adaptability
|
|
2.31431
|
29.7593
|
50
|
Fifth Year
|
|
|
Significant at 0.01
|
3.652
|
15.54629
|
169.6105
|
100
|
Third Year
|
Overall Survey
|
|
10.78259
|
178.3333
|
50
|
Fifth Year
|
|
• The table value for 𝑡 is 2.576 at a significance level of 0.01 and 1.960 at a significance level of 0.05.
The previous table indicates the presence of statistically significant differences in the degree of self-learning skills practiced by students in favor of those in their fifth year, across all sections of the questionnaire, as well as in the overall results. This could be attributed to the fact that the fifth year requires a significant amount of effort, primarily relying on the students themselves to obtain information. Additionally, this stage involves field visits to institutions and interaction with specialists and experts. Furthermore, there is continuous use of computers and the internet to access knowledge and information.
As for the statistically significant differences in the degree of self-learning skills practiced by architectural students attributed to the gender variable in (Syria and the Arab world), the arithmetic means, standard deviations, and the t-value for independent samples were calculated. The following table illustrates these results:
|
Statistical Significance
|
t-value
|
Standard Deviation
|
Mean
|
N
|
Group
|
Questionnaire axis
|
|
Not Significant t
|
0.507
|
2.82996
|
33.6292
|
85
|
Syria
|
Skill of Continuous Inquiry and Thinking
|
|
3.24216
|
33.8833
|
65
|
Other Arab Countries
|
|
|
Not Significant t
|
0.644
|
2.55751
|
28.0674
|
85
|
Syria
|
Skill of Self-Regulated Learning
|
|
2.72978
|
28.3500
|
65
|
Other Arab Countries
|
|
|
Not Significant t
|
1.40
|
3.70128
|
42.3258
|
85
|
Syria
|
Skill of Communication and Collaboration (Group Learning)
|
|
4.13487
|
43.2333
|
65
|
Other Arab Countries
|
|
|
Not Significant t
|
1.190
|
3.24195
|
39.0337
|
85
|
Syria
|
Skill of Experience and Imagination
|
|
3.70566
|
39.7167
|
65
|
Other Arab Countries
|
|
|
Not Significant t
|
0.960
|
3.00735
|
28.6629
|
85
|
Syria
|
Skill of Problem Solving and Adaptability
|
|
3.08537
|
29.1500
|
65
|
Other Arab Countries
|
|
|
Not Significant t
|
1.073
|
13.90225
|
171.7191
|
85
|
Syria
|
Overall Survey
|
|
15.53963
|
174.3333
|
65
|
Other Arab Countries
|
|
• The critical t-value is 2.576 at the 0.01 significance level and 1.960 at the 0.005 significance level.
The previous table indicates that there are no statistically significant differences between architectural students in Syria and the Arab world in acquiring and practicing self-learning skills, both in the overall questionnaire and in all of its sections. This can be attributed to the similarity of architectural design education programs in Syria, Egypt, Iraq, and Yemen, which leads to an equal level of skill acquisition and practice among students in this field.