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Alternative conceptions become obstacles in physics. However, it is difficult to find instruments that can identify students' alternative conceptions, especially in gases kinetic theory (DIGaKiT). The purpose of this research was to development of diagnostic instrument of DIGaKiT in identifying students' alternative conceptions by Rasch analysis model. The research method used the defining, designing, developing, and disseminating (4D). The samples are 31 students (12 male students and 19 female students, their ages were typically 16 years old) at one of the senior high schools at Belitung. Rasch analysis was used to identify the validity, reliability, and distribution of students' alternative conceptions. The result is that the level of validity and reliability of the instrument is in a good category. Meanwhile, alternative conceptions of the kinetic theory of gases can be identified in all questions, and the questions with the highest alternative conceptions are questions with code Q11 (77%) and the lowest are questions with codes Q1, Q5, and Q6 (4%). Therefore, teachers must design learning processes that can reduce students' alternative conceptions of the kinetic theory of gases material.

This study aims to reconstruct Grade 11 students' misconceptions about force through the Conceptual Change Model (CCM) making use of Predict, Discuss, Explain, Observe, Discuss, Explore, Explain (PDEODEE) tasks. This study was conducted using a mixedmethod approach. The participants in this study were 65 students (33 students in the experiment class--13 males and 20 females, and 32 students in the control class--12 males and 20 females) from a high school in Bandung, Indonesia. The instrument test used is the Four-Tier Test-formed Force Concept Inventory (4TT-FCI) with 8 question items. Three analyses were carried out: an analysis of students' misconception profiles during the pre-test and post-test, the reconstruction of students' misconceptions analysed based on percentage and codification using Great Change (GC), Not Change (NC), and Un-Great Change (U-GC). The improvement in students' conception was carried out using N-Gain with three categories (Low, Moderate, and High). The results show that the students' conception profile during the pre-test and post-test still detects misconceptions. However, these misconceptions can be ameliorated using CCM with PDEODEE tasks because the highest conceptual change is in the Misconceptions category (GC= 34.5) and the lowest is in the Un-Code category (U-GC= 2.4). The increase in the correctness of the conception was measured in the experimental class at 0.73 (High category), and the control class is 0.42 (Moderate Category).

Augmented Reality (AR) can positively impact learning and provide authentic experiences in the form of simulations by increasing enthusiasm for learning and activities in the classroom. This research aims to develop the design and effectiveness of the Augmented Reality Greenhouse Effect (ARGE) Integration Model Physics Independent Learning (MPIL) and explore the results of the product and their application in physics learning. The ARGE application will be implemented in universities located in the central part of Indonesia ARGE presents a simulation of learning tools to train lecturers and students with the implementation of AR technology, which aims to transfer real learning experiences to understand the concept of the Greenhouse Effect. The research method chosen in the ADDIE method was carried out on 127 students and integrated with MPIL. The number of these students participated in research, where they were divided into three student groups: (i) Semester 3 (N= 42), (ii) Semester 5 (N= 42), and (iii) Semester 7 (N= 43). After 12 weeks of lectures, most students stated a significant positive confirmation of ARGE implantation. These results revealed that the application of ARGE MPIL based on testing the effects of the product by students had excellent practicality in teaching in relevance with a percentage of 92.38%. Then the self-confidence aspect obtained a percentage of 94.29%, and the satisfaction aspect received a percentage of 97.14%. The ARGE design is integrated with MPIL developed to properly simulate the Greenhouse Effect concept. ARGE is effectively categorized as an excellent medium for learning the Greenhouse Effect concept.