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Digital technology and literacy can heighten the transformation of teaching and learning in higher education institutions (HEIs). This study uncovers the extent to which "digital technologies" have been used to advance the teaching and learning process in HEIs, and the barriers and bottlenecks to why it may not have been effectively implemented across the HEIs. The study used nine selected countries in Latin America (LATAM) based on the main focus of the educators, commercial, and financial investors; to show the level of impact/implications of computer technologies on the teaching and learning processes. We applied a two-step (mixed) methodology (through a quantitative and qualitative lens) for the research investigation, using data collected from survey we administered to faculty members in HEIs across the different countries in LATAM. In turn, we implemented a Text Mining technique (sentiment and emotional valence analysis) to analyze opinions (textual data) given by the participants to help determine challenges and obstacles to using the digital technologies for teaching and learning in the region. Quantitatively, we applied a Kruskal-Wallis H-test to analyze the collected multiple choice and ranked items in the questionnaire in order to identify prominent factors that consummately influence the reach, barriers, and bottlenecks, and where the differences may lie across the different LATAM countries. The results show that the users upheld the emphasis on lack of training, infrastructures and resources, access to internet and digital platforms, as the main challenges to the teaching--learning process. The study also empirically discussed and shed light on critical factors the HEIs, particularly in LATAM, should resolve and adopt in support of the decision-making strategies, operational policies and governance, financial investments, and policymaking, at a time when "digital technologies" have become an inevitable and indispensable part of education and learning.

This study introduces a novel methodology integrating computer vision, visual servo control, and the Kalman Filter to precisely estimate object locations for a 3-RRR planar type parallel manipulator. Through kinematic analysis and the development of a vision system using color indicators, the research enhances the ability of the manipulator to track object trajectories, especially in cases of occlusion. Employing Eye-to-Hand visual servo control, the research further refines the visual orientation of the sensor for optimal end effector and object identification. The incorporation of the Kalman Filter as a robust estimator for occluded objects underscores the predictive accuracy of the system. Results demonstrate the effectiveness of the methodology in trajectory generation and object tracking, with potential implications for improving robotic manipulators in dynamic environments. This comprehensive approach not only advances the fields of kinematic control and visual servoing but also opens new avenues for future research in complex spatial manipulations. [ABSTRACT FROM AUTHOR]

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