In today’s digital age, new technological tools are increasingly becoming an indispensable part of the educational process, particularly in educating children. The development of technology, including tablet computers, and mobile phones, offers numerous opportunities for enhancing teaching methods and fostering children’s development. These technologies offer access to a wide array of digital resources, interactive content, and personalized educational experiences, thereby opening up new methods in education. However, despite the benefits, many studies underscore the potential negative impacts of utilizing new technologies in children’s education. For the above reasons, a study was conducted to examine how new technologies influence children’s learning of geometric shapes. Forty children, evenly distributed by gender and place of residence, participated in the study, undergoing testing using both mobile phones and Tablet PCs. The results revealed statistically significant differences based on the respondents’ gender, place of residence, and the devices through which the tasks were presented, particularly for certain geometric shapes.
Course evaluation, a critical component for the implementation of outcome-based education (OBE), provides substantial data support. The reliability, validity, and discriminative power of evaluation results are significantly influenced by the choice of course evaluation methods. An effective course evaluation method identifies weak links in the teaching process, offering a foundation and reference for continuous course improvement. This study introduces a course evaluation method based on achievement pathways, establishing the supportive relationship among course-related graduation requirement indicators, course objectives, and achievement pathways. Grounded on formative assessment, a system to quantify the achievement of teaching objectives in courses is constructed. The method has been applied to courses, such as Data Visualization and Software Engineering, at the Beijing Institute of Petrochemical Technology. Practice demonstrates that this method is capable of identifying weaknesses in the course implementation process, providing theoretical foundation and reliable assurance for ongoing course improvement.
The widespread adoption of Learning Management Systems (LMSs) in educational contexts, underscored by their critical role in facilitating cloud-based training across diverse settings, serves as the foundation of this investigation. In the era of increasing integration of technology within higher education, a notable reduction in the costs associated with the creation of online content has been observed. The shift towards remote learning, precipitated by the COVID-19 pandemic, has highlighted the indispensable nature of LMSs in the delivery of specialized content, the application of varied pedagogical strategies, and the promotion of student engagement. Adaptability, defined as the ability to adjust behavior, cognition, and emotional responses in the face of new circumstances, has been recognized as a key factor in the success of online learning. This study employs sophisticated Machine Learning Techniques (MLTs) to explore the determinants of student adaptability, introducing the novel framework of Online Learner Adaptability Assessment using MLTs (OLAMLTs). Through the analysis of comprehensive datasets, which include indicators of student behavior, performance, and engagement within online platforms, MLTs facilitate the identification of patterns and correlations pertinent to adaptability. The OLAMLTs framework applies a retrospective analysis to variables such as technological proficiency, motivation, and self-regulatory capabilities, enabling the provision of customized recommendations for educators. By facilitating targeted educational interventions, the study seeks to address the disparity between the need for adaptable learners and the availability of tools designed to foster this critical attribute. The ultimate aim is to augment the resilience and efficacy of online learning platforms in anticipation of future disruptions, including pandemics or other unforeseen challenges. This research contributes to the ongoing efforts to develop a more adaptive and resilient online learning landscape, marking a significant advancement in the fields of educational technology and pedagogy.
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