The aim of this paper is to determine the influence of blended learning environments on self-regulated and self-directed learning skills of undergraduate students. The explanatory sequential mixed method was used. In total 167 students participated in the study. While sixty students taking “Programming Languages” course at Computer Education and Instructional Technologies Department constituted the experimental group, 102 undergraduates-65 of them from the same department (Control 1) and 42 from Electronic Engineering Department (Control 2) formed the control groups. Self-directed Learning Readiness Scale, Self-regulated Learning Scale and semi-structured interviews were used as data collection instruments. While the experimental group received blended instruction, control groups received traditional instruction for weeks. The findings of the study revealed that self-regulated and self-directed scores of experimental group differed significantly from the control groups` indicating that the use of blended instruction is more effective than traditional instruction in terms of developing self-regulated and self-directed learning skills. Students in the experimental group pointed out that the blended learning environment presented rich content, easy accessibility, effective guidance and motivation.

The objectives of this study were to analyze the validity, practicality, and effectiveness of South Kalimantan local wisdom-based biology learning and its effect on student learning outcomes. The research method used is research and development. This research was in a Develop stage of Thiagarajan’s Model. This development has produced learning models (lesson plans, student’s worksheet, learning achievement test questions, teacher activity sheets, student activity sheets, and student response sheets). The local wisdom-based learning model were designed with seven stages using Banjar language (regional language of South Kalimantan). Model that have been developed were tested for the level of validity, practicality, effectiveness, and its effect in learning. The level of validity is determined based on the assessment and review of the four validators. To find out the effectiveness and the effect of the learning model, quasi-experimental design was applied by involving two classes at SMAN 7 Banjarmasin-Indonesia. Data were collected using a variety of instruments, namely the validity assessment sheet, the student’s worksheet and lesson plan sheets, student achievement test questions, and student response sheets. Data analysis was implemented to measure the effectiveness and the effect of learning by calculating n-Gain and ANCOVA, respectively. The results, the learning tools met the "valid" criteria so that it can be implemented. Learning also concluded having good practicality criteria. Moreover, it can be seen that the application of local wisdom-based learning model and tools was quite effective in improving student learning outcomes, in contrast to learning in the control class. Furthermore, ANCOVA test concluded that there were significant differences in learning outcomes between students in the experimental and the control class.

Teachers who can adapt and be ready for all changes will also be able to provide a balance to increase the competence of vocational high school students. This is also not denied when teachers become assessors in student competency tests. The objectives of this study were to produce an instrument for the readiness of teachers as assessors; to knowing good grain reliability; to know the characteristics of the instrument; and to know the difficulty level of the item. The method used in this research is instrument development. Respondents were vocational school teachers who were candidates for competency test assessors. Data collection techniques using a questionnaire. Analysis of construct validity using Confirmatory Factor Analysis. Reliability using Cronbach’s alpha. Test the instrument items using the Rasch model. The results are the readiness instruments of the vocational teacher as an assessor has 19 indicators that have been grouped into 5 factors with consistency values being in the same construct (proven construct validity). The result of the calculation of the reliability of this instrument is 0.852, which means that the reliability coefficient is high; There are two items, namely numbers 24 and 18 which indicate the absence of a fit item in the overall item fit criteria; At the item difficulty level, items 8 and 6 have a difficulty score of more than 2, while this indicates that items 8 and 6 have a high difficulty level.

The pandemic case has shifted away from face-to-face teaching to online blended learning. This phenomenon certainly causes various problems in the world of education. The online blended learning is good when applied with good internet connections and complete facilities. However, it differs from Indonesian coastal students who do not have supporting facilities. Therefore, this research aims to analyze the experience and readiness of Indonesian coastal students. It determines the facilities of the process using qualitative research with a phenomenological approach. Purposive sampling was used to collect data from 25 students living in coastal areas in Aceh, Indonesia. Furthermore, in-depth interviews were used to obtain instruments and techniques for data collection, observations, field notes, and audio-visuals. Data analysis was carried out qualitatively by reducing, displaying, drawing conclusions, and verifying data. The data processing was conducted using NVivo 12 plus software. The kappa coefficient is used to check the accuracy of the data since there was no bias during coding. The analysis results show that Indonesian coastal students are not ready to conduct the online blended learning process. Furthermore, it is recommended that future research focus on coastal students’ development. A Hypothetical Learning Trajectory design should be created to assist in independent learning and lessen their readiness.

Learning activities are conducted to help students achieve optimal academic achievement. This research aims to optimize student academic achievement through a learning process that integrates comprehensive formative assessments, including formative tests, self-assessment, peer assessment, and the initiator of creating summaries or concept maps that are given to students in a structured manner at the end of every lesson. The research method used was a quasi-experimental method with a 2x2 factorial design. Students enrolled in the biology education program of the basic physics course for the 1st semester of the 2019 academic year participated in this study. The participants were 66 undergraduate students divided into two classes. Thirty-four students in the experimental group were in class A, while 32 students in the control group were in class B. Data were collected using a learning outcome test instrument to measure academic achievement, which was tested at the end of the semester. Data were analyzed using a two-way ANOVA. This study concluded that a learning process that includes comprehensive formative assessment significantly affects students' academic achievement. These findings support the theory that formative assessment provides feedback, correction, and improvement in student learning.

The Indonesian government has declared a strong commitment to information and communication technology (ICT) education reform but has made meager progress due to inconsistent education policies, fragmentary technological infrastructure, and ill-prepared teachers. Despite these obstacles, young people in Indonesia have embraced smartphones and related technologies as important means of maintaining their socially integrated lifestyles. This project sought to measure the adoption of smartphone technologies among pre-service teachers as part of their broader ICT consciousness and teaching. We examined the ICT competencies of 220 pre-service teachers at two state universities in western Indonesia. A questionnaire was distributed to the participants toward the end of the students' final practicum during the COVID-19 closure of the schools. Results showed very high use of smartphones in private contexts, infrequent use of laptops and desktop computers, a strong rejection of institutionally available (or often unavailable) devices and services, and a skewing of ICT skills toward tools available on smartphones, especially those accessible through social media platforms.

The study aimed to explore the self-directed learning readiness model and its relationship with various factors such as emotional intelligence, transformational parenting, need-supportive teaching style, and self-efficacy as potential mediators. The research was conducted with 415 junior high school students in Surabaya, Indonesia. To ensure the reliability and validity of the instruments used in the study, confirmatory factor analysis was performed. The loading factor values of all the items in the instruments were found to be greater than .50 indicating a satisfactory level of validity. Additionally, the reliability coefficient of all the instruments exceeded .90 demonstrating good internal consistency. Analysis using structural equation modeling (SEM) demonstrated that the theoretical model of self-directed learning readiness was consistent with empirical conditions because it meets the standard value of goodness of fit. Furthermore, through the indirect effect tests, it was discovered that need-supportive teaching style, emotional intelligence, and transformational parenting significantly influenced self-directed learning readiness, with self-efficacy acting as a mediator. Among the factors examined, self-efficacy was found to have the greatest impact in explaining readiness for self-directed learning readiness.

Artificial intelligence (AI) has revolutionized higher education. The rapid adoption of artificial intelligence in education (AIED) tools has significantly transformed educational management, specifically in self-directed learning (SDL). This study examines the factors influencing Indonesian higher education students' intention to adopt AIED tools for self-directed learning using a combination of the Theory of Planned Behavior (TPB) with additional theories. A total of 322 university students from diverse academic backgrounds participated in the structured survey. This study utilized machine learning it was Artificial Neural Networks (ANN) to analyze nine factors, including attitude (AT), subjective norms (SN), perceived behavioral control (PBC), optimism (OP), user innovativeness (UI), perceived usefulness (PUF), facilitating conditions (FC), perception towards ai (PTA), and intention (IT) with a total of 41 items in the questionnaire. The model demonstrated high predictive accuracy, with SN emerging as the most significant factor to IT, followed by AT, PBC, PUF, FC, OP, and PTA. User innovativeness was the least influential factor due to the lowest accuracy. This study provides actionable insights for educators, policymakers, and technology developers by highlighting the critical roles of social influence, supportive infrastructure, and student beliefs in shaping AIED adoption for self-directed learning (SDL). This research not only fills an important gap in the literature but also offers a roadmap for designing inclusive, student-centered AI learning environments that empower learners and support the future of SDL in digital education.