Adaptive Teaching Research Articles

EComplexity: validation of a complex thinking instrument from a structural equation model

The eComplexity instrument aims to measure the perception of achievement in the complex thinking competency and its sub-competencies. To ensure the reliability of this instrument, validation processes like the one presented in this article are necessary. Methodologically, this study evaluates data from 1,037 university students in Mexico, confirming the statistical validity and reliability of the instrument. As a result, the demonstrated reliability of the eComplexity instrument as a tool for measuring perceived achievements in complex thinking provides a valuable resource for assessing the effectiveness of educational interventions. Consequently, this research contributes to a more informed approach to fostering critical thinking skills, benefiting both theoretical exploration and practical application in educational settings. The study employs the Partial Least Squares Structural Equation Modeling (PLS-SEM) to evaluate students’ self-perceptions of their performance in complex thinking and its sub-competencies, thus advancing the field of educational measurement. Academically, it enriches the discourse on the design and validation of instruments, offering a rigorous model for future efforts in measuring cognitive competencies. Practically, the study’s results inform educational practice by identifying systemic and scientific thinking as key to developing complex thinking skills. This knowledge enables educators to more effectively adapt teaching strategies and curricular designs, aiming to enhance students’ ability to navigate the complexities of the modern world.

Comparing Finnish and Chinese national teacher education frameworks from the teacher competency perspective

ABSTRACT Finnish and Chinese teacher education have gained worldwide attention because of their pupils’ significant achievements in international assessments. Focusing on the manifestations of teacher competencies in the respective teacher education frameworks, this article compares Finnish and Chinese teacher education and their curricular traditions. The mixed-method analysis of the two national frameworks draws attention to significant differences and similarities. Due to particular cultural contexts, while the Chinese Framework emphasises ethics, student management, and assessment competencies, Finnish teacher education focuses comparatively more on adaptive teaching, innovation, and partnering. The competencies of subject matters, pedagogy and subject didactics, teaching technologies, communication, multidisciplinarity, reflection and inquiry, and professional development are emphasised in both countries. This article provides insights into manifestations of teacher competencies in the context of hybrid curriculum traditions in Finland and China through adapting and applying an international framework, offering alternative perspectives on quality teacher education beyond Anglo-American approaches.

Student-centered learning in the digital age: in-class adaptive instruction and best practices

<span lang="EN-US">Adaptive instruction is a promising solution to the limitations of traditional classroom instruction, which assumes that all students learn in the same way and at the same pace. Adaptive instruction tailors the learning experience to each student’s needs and abilities. Several adaptive instruction tools and platforms exist, including intelligent tutoring systems, learning management systems, mobile apps, AI chatbots, and adaptive machine-learning programs. The Adaptive Instruction of Student Control Theoretical Framework suggests that allowing students to control their use of learning resources leads to better learning outcomes. Implementing adaptive instruction in higher education can be difficult due to faculty buy-in, technical infrastructure, and student motivation. Effective instructional design is crucial for adaptive instruction to support student control and maximize benefits. Overall, instructors must pay attention to student motivation and work to create learning environments that foster motivation, autonomy, and engagement to implement adaptive instruction successfully.</span>

Teachers’ Perspectives on the Education Process: Identifying Challenges and Promoting Sustainable Solutions

Abstract The responsibilities of a teacher are diverse and intricate. Societal shifts, political developments, and rapid technological progress have added further layers of complexity to teachers’ daily tasks. The current research endeavors to analyze how teachers, with varying levels of experience and backgrounds, adapt to these changes in education and perceive opportunities for further development. The aim of the article is to study Latvian teachers’ perspectives on education in Latvia and identify areas for improvement. To reach the aim, focus group discussion was conducted involving six teachers from diverse backgrounds. Through content analysis, the study identified the primary challenges facing the current education process in Latvia: 1) prolonged, ineffective educational reforms; 2) challenges in rural education; 3) inappropriate teacher training; 4) the need for adaptive teaching methods; 5) the importance of cooperation among teachers and with parents. Addressing these areas could lead to significant improvements in the Latvian education system. The analysis sheds light on several issues within education, including the dynamics of teacher–pupil roles, the quality of educational outcomes, and pupil attitudes.

Strategi Asesmen Kebutuhan Siswa di Sekolah Menengah Pertama: Perancangan Berbasis Data dan Analitik

This study aims to design a data-driven and analytical-based strategy for assessing student needs in Junior High School (JHS). A qualitative approach was employed, utilizing observation and literature review methods. The study population consisted of JHS students, with samples randomly selected from various schools. Research instruments included social media observation and literature review. Instrument validity and reliability were ensured through literature comparison. Data were analyzed through data reduction and triangulation approaches. The results indicate that JHS student needs assessment aims to measure learning achievement, provide feedback, promote active learning, adapt teaching methods, assess program effectiveness, and identify special needs. Assessment principles, types, data-driven design, and needs analytics are the main focuses. The implications of this research are to enhance the quality of education in JHS through more responsive and effective assessments. Suggestions for further research include involving more educational stakeholders to ensure program relevance and responsiveness. This study contributes to the development of better education in Indonesia.

Synergetic approach platform in organising methodological activity at school

Relevance. The research relevance is determined by the interest of teachers� application of modern innovative education system, and their involvement in the learning process with the help of a diverse and new approach in education. Purpose. The study aims to investigate the basics of the synergetic method of teaching, and its application in the educational process of the school. Methodology. The study utilized questionnaires and assessments to explore how the synergetic approach is applied by 36 teachers in Taldykorgan City, Kazakhstan. Methodological approaches included self-assessment, creative potential tests, and a seminar on synergetic education principles, supported by methods like abstraction, analysis, synthesis, and axiomatic reasoning to assess its educational impact. Results. The results of the study indicate varying levels of engagement and adaptation to the synergetic approach among secondary school teachers in Taldykorgan, Kazakhstan. Younger teachers demonstrated a keen interest in innovation and regularly incorporated new technologies into their teaching practices. Teachers with moderate experience exhibited a strong commitment to professional development through regular self-education activities. However, teachers with extensive experience showed less enthusiasm for adopting innovative practices, preferring traditional curricula. Overall, the implementation of the synergetic approach facilitated collaborative problem-solving and knowledge exchange among teachers, underscoring its potential to enrich educational methodologies and foster a dynamic learning environment. Conclusions. In conclusion, the study underscores the transformative impact of the synergetic approach on methodological activities within school settings, particularly in enhancing teachers' professional development and fostering innovative educational practices. The findings highlight that integrating synergetics into pedagogical frameworks enhances educators' abilities to navigate complex educational challenges, collaborate effectively, and adapt teaching methodologies to suit diverse learning needs. This research underscores the importance of ongoing support and training in synergetic pedagogy to sustain its benefits in improving educational outcomes and promoting continuous professional growth among teachers. Keywords: synergetic approach; multivariability; research competence; self-organisation; teacher�s professional status; methodological activity

Using Genetic Algorithms to Automate Scenario Generation and Enhance the Training Value of Serious Games for Adaptive Instruction

This paper discusses an end-to-end process to enhance the variability of serious game scenario conditions to support adaptive instructional strategies that select changes in sce-nario difficulty to match learning objectives to trainee ca-pabilities. This process can also be used to model or recog-nize human responses to serious game stimuli to support trainee feedback during after-action reviews (AARs). Adaptive instruction is a learning experience where inter-ventions (content selection and feedback) are tailored for each individual trainee or group of trainees. Adaptive train-ing has been shown to be as much as one to two standard deviations more effective than traditional classroom meth-ods. Our process starts with a few parent scenarios. The population of parent scenarios is automatically expanded using a Novelty search (genetic algorithm) methodology to optimize feature variability in the game-based scenarios. Specifically, this paper focuses on the process of creating new training scenarios of varying difficulty and conditions based on changes in scenario environmental factors (i.e., light, precipitation, wind, and cloud cover). The resulting new scenarios may then be run within a serious game with embedded intelligent agents to represent realistic entity behaviors under the scenario-specified conditions. The ability to morph conditions and scenario difficulty during an adaptive training event is a significant benefit of this process.

The transformative potential of Artificial Intelligence for Education

Education today faces a range of challenges, but also unique opportunities, vis-à-vis the evolution of digital technologies. Traditional teaching methods struggle to meet the diverse needs of students, as classrooms comprise learners at different levels. The Education AI project represents an initiative aimed at integrating Artificial Intelligence (AI) into the classroom to address the diversity of students and the challenges faced by traditional teaching methods. The project's core objective is to enhance student learning outcomes by providing an adaptive and personalised learning experience, thereby making education more equitable and effective. This paper evaluates the project's impact on student learning, teacher workload, and its broader applicability in education. The study's methodology combines quantitative and qualitative data, employing a mixed-methods approach to provide a comprehensive analysis of the Education AI system's effectiveness. Preliminary findings indicate a notable improvement in student performance, particularly among low and medium-performing students, with quantitative data revealing an average improvement of 23% in assessments for low-performing students. The system's user-friendly interface, gamified elements, and immediate feedback mechanisms have been well-received, with a majority of students reporting enhanced engagement and understanding of mathematical concepts. Teachers have also reported positive experiences, highlighting the system's role in reducing their workload and facilitating personalised and adaptive teaching and learning. Qualitative feedback from interviews with teachers and students provides further insights into the system's impact, emphasising its varied and engaging question types, adaptivity, and the shift from paper-based to digital learning. The feedback also reveals a desire for expansion to other subjects and enhancements in the system's analytics for more targeted support.The Education AI project demonstrates the transformative potential of AI in the classroom, with significant improvements in student performance and positive reception from both students and teachers. The study highlights the importance of addressing technical challenges and expanding the system's capabilities for broader application. The project offers valuable insights into the future of education, where technology and human expertise converge to create a more personalised, adaptive engaging, and effective learning experience for all students. This initiative, underpinned by the transformative potential of AI for education, aims and informing and guiding future innovations in educational technology.

Orchestrating vocational education classrooms for adaptive instruction and collaborative learning

Orchestrating vocational education classrooms for adaptive instruction and collaborative learning

Using Reinforcement Learning Algorithms to Optimize Practical Skills Development in Higher Vocational and Technical Education

Optimizing practical skills development in higher vocational and technical education involves a multifaceted approach. Firstly, curriculum design should integrate hands-on learning experiences, industry-relevant projects, and internships to bridge the gap between theoretical knowledge and real-world application. Secondly, institutions should invest in state-of-the-art facilities, equipment, and technology to provide students with a simulated work environment conducive to skill mastery. This paper, explored the integration of reinforcement learning algorithms within the Seahorse Optimization Probability Education (SHOPE) framework to optimize practical skills development in higher vocational and technical education. Through extensive experimentation and analysis, we investigate the effectiveness of various reinforcement learning algorithms in enhancing vocational teaching strategies, skill assessment processes, and classification tasks within educational contexts. Our findings highlight the capability of SHOPE to iteratively refine teaching methodologies, leading to significant improvements in student skill acquisition, success rates, and classification accuracy over multiple epochs. With the adaptive teaching strategies, and optimized vocational education programs tailored to individual student needs. For instance, our results demonstrate an average skill improvement ranging from 35% to 65% across different reinforcement learning algorithms. Moreover, success rates for mastering targeted skills reach levels between 75% and 92%.

Evolving engineering education: online vs. in-person capstone projects compared (EEE-OIPC)

This study examines the effectiveness of online and face-to-face (F2F) instructional methods in Capstone Senior Design (CSD) projects within Electrical Engineering (EE) and Mechanical Engineering (ME). It explores how each mode influences student success and learning outcomes, addressing the need for adaptable teaching strategies in science, technology, engineering, and mathematics (STEM) education. A comprehensive assessment was conducted, which included project evaluations, advisor feedback, and self-peer reviews. This multifaceted approach aimed to gauge the relative efficacy of online versus F2F modalities in supporting educational outcomes. The findings indicated that both online and F2F modalities achieved parity on several metrics. However, F2F settings significantly enhanced teamwork and collaboration among students. In contrast, online environments excelled in advisor evaluations, suggesting effective mentorship despite less consistent teamwork and project execution. The results emphasize the potential benefits of integrating online and traditional pedagogies to improve educational strategies and student learning experiences. The study highlights the importance of developing online instructional strategies that better mimic the collaborative advantages of F2F instruction. It also underscores the need for a holistic approach to curriculum development to prepare STEM students effectively for future challenges.

Engaging students via interactive lecture activities inspired by common classroom practice

This article summarises the author’s experience transitioning from Further Education (FE) to Higher Education (HE) teaching in 2022-23. It identifies areas for concern in the author’s setting and outlines the author’s strategies for overcoming these obstacles, utilising their background in FE. In particular, this article explores common, engaging classroom activities and outlines why these activities require adapting for use in HE. Inspired by these classroom activities, this article presents a selection of interactive lecture activities promoting student engagement via formative assessment, adaptive teaching, and student ownership. It summarises how the activities have evolved over time and reflects on their use. Finally, the author reviews the success of the activities, discusses students’ reactions to them, and outlines future plans.

Exploring the Complexity of Adaptive Teaching Expertise within Knowledge Generation Environments

The shift towards Next Generation Science Standards represents a paradigmatic change in teaching, transitioning from knowledge transmission to knowledge generation approaches. This reform underscores the complexity of teaching expertise, extending beyond mere knowledge to require a profound comprehension of generative learning environments. In this study, we explore Adaptive Teaching Expertise (AdTex), defining it as a teacher’s capacity characterized by fluidity and reflexiveness in teaching dynamics, rather than just flexibility. Through a complexity framing approach, we delineate three layers of AdTex: the visible actions of teachers, the semi-visible use of epistemic tools such as language, dialogue, and argument, and the tacit orientations towards learning that encompass epistemological, ontological, and axiological dimensions. Our research primarily investigates the intricate relationship between the epistemic tool and orientation layers. Our findings highlight the significance of an interconnected understanding and the impact of philosophical orientations on adaptive teaching practices. A notable contribution of this study is the development of a framework that articulates the belief and knowledge systems crucial for fostering generative learning environments, alongside the introduction of complexity maps to illustrate the interplay among these subsystems.

Exploring the effectiveness of online learning tools and technologies while teaching Maritime English to future ship engineers

Maritime English proficiency is crucial for future ship engineers to effectively communicate, operate, and ensure safety in the globalised marine industry. The study is devoted to analysing the integration of language and technical skills, highlighting their symbiotic relationship in the educational context. This paper explores the development of modern approaches to teaching Maritime English, emphasising continuous assessment and adapting teaching strategies. The assessment and evaluation methods were used to measure language proficiency, demonstrating the importance of ongoing assessment to monitor progress and adapt teaching strategies. Additionally, this article examines the influence of e-learning and digital resources, shedding light on advancements, challenges, and opportunities in Maritime English education. The importance of cross-cultural communication training is discussed, emphasising its role in preparing future ship engineers for an international working environment on a ship. Case studies, best practices, and lessons conducted at Kherson State Maritime Academy (KSMA), Ukraine, are shared to provide practical insights for teachers. The implications of international language proficiency regulations in the maritime industry are also addressed. By analysing the impact of these pedagogical approaches on ship engineers' safety and crisis management capabilities, this article highlights the tangible benefits of effective Maritime English education. For mobile learning app developers, the study suggests integrating features that promote collaborative learning, interactive assessments, and personalised feedback to optimise learning experiences. Overall, integrating online learning tools and technologies (e.g. Moodle LMS) presents a promising avenue for advancing Maritime English education and preparing future ship engineers for the challenges of the marine industry today.

Pengaruh Manajemen Kelas Inklusif terhadap Prestasi Belajar Siswa Sekolah Dasar

In the current educational context, the effectiveness of inclusive classroom management in improving student learning achievement in elementary schools has become an urgent topic for research. This study aims to analyze the influence of inclusive classroom management on student learning achievement, considering variables such as adaptive teaching strategies, support for the learning environment, and dynamics of student interaction. Using quantitative methods with a survey research design, this study involved a sample of 40 elementary school students from the city of Bima, selected through purposive sampling technique, considering the specific characteristics of the population studied. Data were collected using questionnaires and analyzed using descriptive statistics and linear regression tests to determine the impact of inclusive classroom management on learning achievement. The results show a significant positive effect of inclusive classroom management on student learning achievement, reaffirming the importance of adapting teaching strategies and creating a supportive learning environment in inclusive classrooms. This conclusion supports the argument that effective inclusive classroom management practices are essential for improving student learning outcomes. Based on these findings, this study recommends enhancing teacher capacity through continuous professional training in inclusive classroom management and the development of a more inclusive curriculum to support the learning success of all students.

Research on the Application of Improved Apriori Algorithm in Sport-Adaptive Online Teaching System Under Big Data Environment

Each student in an adaptive education system has significant differences in knowledge background, ability level and cognitive style. Therefore, to build an adaptive teaching system, it is necessary to establish an operable, reasonable and individualized student model by clarifying students’ abilities and differences. The improved Apriori algorithm under big data is the most classic association rule algorithm, which is generated by a set of candidates, and it uses the iterative method of hierarchical search to traverse a set of frequency items in the transaction database. After finding the set of frequency items, select the association according to the trust rules. This paper studies how to apply the improved Apriori algorithm to an adaptive online education system in a big data environment. An evolutionary algebra is taken with mean fit of 80, population size of 20, mean fit of 0.28, population size of 60, mean fit of 0.26, population size of 80, mean fit of 0.25, mean population size of 0.25. The population size is 200, and the average fitting is 0.24. The larger the error, the smaller the error between each indicator of the test paper and the corresponding value specified by the user. The improved Apriori algorithm in the big data environment has designed five themes of rule mining, which are mainly used for class management: class linkage, class category linkage, student basic information linkage, lecture and basic information linkage, and lecture mode linkage. They play the role of teaching assistants with a specific role.

Teaching through their eyes: effects on optometry teachers' adaptivity and students' learning when teachers see students' gaze.

Adaptive teacher support fosters effective learning in one-to-one teaching sessions, which are a common way of learning complex visual tasks in the health sciences. Adaptive support is tailored to student needs, and this is difficult in complex visual tasks as visual problem-solving processes are covert and thus cannot be directly observed by the teacher. Eye-tracking apparatus can measure covert processes and make them visible in gaze displays: visualizations of where a student looks while executing a task. We investigate whether live dynamic gaze displays help teachers in being more adaptive to students' needs when teaching optical coherence tomography interpretation in one-to-one teaching sessions and whether this fosters learning. Forty-nine students and 10 teachers participated in a one-to-one teaching session in clinical optometry. In the control condition, teachers saw the learning task of the student and could discuss it with them, whereas in the gaze-display condition, teachers could additionally see where the student looked. After the 15-minute teaching session, a test was administered to examine achievement. Furthermore, students filled in the 'questionnaire on teacher support adaptivity', and teachers rated how adaptive their support was. Bayesian analyses provide some initial evidence that students did not experience support to be more adaptive in the gaze-display condition versus the control condition, nor were their post-test scores higher. Teachers rated their provided support as being more adaptive in the gaze-display versus the control condition. Further research could investigate if live dynamic gaze displays impact adaptive teaching when used over longer periods or with more teacher training.

Automated Teaching Weighted Recurrent Neural Network (Atwrnn) Model: Analysis of Badminton Teaching Mode Based on Online Teaching Platform

An online teaching platform serves as a virtual environment where educators and learners interact, collaborate, and engage in various educational activities. Through a combination of multimedia resources, interactive tools, and communication features, online teaching platforms facilitate effective remote learning experiences. Educators can create and deliver engaging instructional content, including video lectures, presentations, quizzes, and assignments, tailored to the needs and preferences of learners. These platforms often incorporate features such as discussion forums, live chat, and virtual classrooms, enabling real-time communication and collaboration among students and instructors. This paper presents an analysis of the badminton teaching mode facilitated by an online teaching platform, augmented with an Automated Teaching Weighted Recurrent Neural Network (ATwRNN). Through this innovative approach, the traditional method of badminton instruction is enhanced by leveraging advanced machine learning techniques to personalize and optimize the teaching process. The online teaching platform provides a virtual environment where instructors can deliver interactive lessons, instructional videos, and practice exercises tailored to individual learner needs. ATwRNN, a specialized neural network model, dynamically adjusts the teaching weightings based on student performance data, providing personalized feedback and adaptive instruction in real time. Simulation results stated that learners who received instruction through the ATwRNN-enhanced platform demonstrated a 25% increase in shot accuracy compared to those in traditional teaching modes. Additionally, the adaptive nature of ATwRNN led to a 30% reduction in the time required for skill acquisition, as learners received personalized feedback tailored to their individual learning pace and preferences. Moreover, user feedback surveys revealed high levels of satisfaction and engagement among participants, with 90% reporting that the ATwRNN-enhanced teaching mode improved their overall learning experience.

Toward Artificial Intelligence-Human Paired Programming: A Review of the Educational Applications and Research on Artificial Intelligence Code-Generation Tools

Pair Programming is considered an effective approach to programming education, but the synchronous collaboration of two programmers involves complex coordination, making this method difficult to be widely adopted in educational settings. Artificial Intelligence (AI) code-generation tools have outstanding capabilities in program generation and natural language understanding, creating conducive conditions for pairing with humans in programming. Now some more mature tools are gradually being implemented. This review summarizes the current status of educational applications and research on AI-assisted programming technology. Through thematic coding of literature, existing research focuses on five aspects: underlying technology and tool introduction, performance evaluation, the potential impacts and coping strategies, exploration of behavioral patterns in technological application, and ethical and safety issues. A systematic analysis of current literature provides the following insights for future academic research related to the practice of “human-machine pairing” in programming: (1) Affirming the value of AI code-generation tools while also clearly defining their technical limitations and ethical risks; (2) Developing adaptive teaching ecosystems and educational models, conducting comprehensive empirical research to explore the efficiency mechanisms of AI-human paired programming; (3) Further enriching the application of research methods by integrating speculative research with empirical research, combining traditional methods with emerging technologies.

Hybrid Teaching Model of College English Based on Collaborative Filtering Recommendation Algorithm

A recommendation system is a powerful tool that analyzes user preferences and behaviors to provide personalized suggestions or recommendations. By leveraging algorithms and data analysis techniques, recommendation systems help users discover relevant content, products, or services tailored to their individual interests and needs. Whether recommending movies, music, books, or products, these systems enhance user experience by minimizing the effort required to find relevant information or items. Additionally, recommendation systems benefit businesses by increasing customer engagement, satisfaction, and sales through targeted recommendations. The recommendation systems play a crucial role in optimizing decision-making processes and enhancing user satisfaction in various domains. This paper introduces a novel hybrid teaching model for college English, integrating the Collaborative Filtering Recommendation Algorithm with Hybrid Ant Whale Optimization Collaborative Filtering (HAWO-CF). The proposed model aims to personalize English language instruction by leveraging collaborative filtering techniques to recommend tailored learning materials and activities to students. Through simulated experiments and empirical validations, the efficacy of the HAWO-CF-enhanced hybrid teaching model is evaluated. Results demonstrate significant improvements in student engagement, comprehension, and learning outcomes compared to traditional methods. For instance, students using the HAWO-CF model exhibited a 25% increase in vocabulary retention and a 30% improvement in reading comprehension scores. Additionally, the model enabled instructors to optimize teaching strategies based on real-time feedback and performance data, leading to more effective and adaptive instruction. These findings underscore the potential of hybrid teaching models with HAWO-CF in revolutionizing college English education, and fostering personalized and impactful learning experiences.