Transformation and digital challenges in Peru during the COVID-19 pandemic, in the educational sector between 2020 and 2023: Systematic Review

Alvarado-Acosta, Anali; Fernández-Saavedra, Jesús; Meneses-Claudio, Brian

doi:10.56294/dm2024232

Cited by 2 publications

(1 citation statement)

References 45 publications

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“…2024, 14, 605 2 of 13 students' needs and fostering their learning [5,6]. In this regard, education offers a unique perspective, emphasizing a deep connection of the student with their educational circle, which further underscores the relevance of care in the educational process [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Design and Psychometric Properties of the Student Perception of Teacher Care Scale in University Students

Dávila-Villavicencio,

Salinas Arias,

Casildo Bedón

et al. 2024

Education Sciences

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Teacher care in the university setting is crucial for the academic, emotional, and social development of students, encompassing moral virtues such as compassion and professional competence. The students’ perception of teacher care directly relates to their well-being and active participation in learning. Despite the recognized importance of teacher care, there is a lack of adequate instruments to measure it, especially in specific cultural and educational contexts like Peru. The aim of this research is to develop and assess the psychometric properties of a scale measuring student perception of teacher care in the Peruvian university context, to provide a valid and reliable tool for future research and educational practices. An instrumental study was conducted with 910 university students aged between 18 and 50 years (M = 20.2, SD = 3.45). The Student Perception of Teacher Care Scale (SPTCS) was used, divided into five dimensions (Compassion, Competence, Confidentiality, Trust, and Awareness). Exploratory (EFA) and confirmatory (CFA) factor analyses were conducted to evaluate the scale’s internal structure, along with reliability analyses and measurement invariance across genders. The EFA identified a four-factor structure reflecting the dimensions of Confidentiality and Trust, Competence, Awareness, and Compassion. The CFA confirmed this structure with good fit indices for four-factor models, which was then adjusted to a five-factor model, one of which is a second-order factor (χ2 = 720.727, df = 369, CFI = 0.951, TLI = 0.946, RMSEA = 0.046, and SRMR = 0.032). Internal reliability was high (α and ω > 0.9 for all factors). Measurement invariance was established across genders, allowing for valid comparisons between men and women. It is concluded that the Student Perception of Teacher Care Scale proves to be a valid and reliable instrument for measuring teacher care in the Peruvian university context. The results emphasize the multidimensionality of teacher care and its significance for the educational environment and student experience. This study contributes to educational research and teaching practice, offering a means to assess and improve caring relationships in higher education.

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Section: Introductionmentioning

confidence: 99%

Design and Psychometric Properties of the Student Perception of Teacher Care Scale in University Students

Dávila-Villavicencio,

Salinas Arias,

Casildo Bedón

et al. 2024

Education Sciences

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Interaction between neuroscience and happiness: assessment from Artificial Intelligence advances

Eslava-Zapata,

Sánchez-Castillo,

Chacón-Guerrero

2024

EAI Endorsed Trans Perv Health Tech

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INTRODUCTION: In recent years, there has been a convergence between Artificial Intelligence and neuroscience, particularly in studying the brain and developing treatments for neurological disorders. Artificial neural networks and deep learning provide valuable insights into neural processing and brain functioning. Recent research tries to explain how neural processes influence an individual's happiness. OBJECTIVES: To evaluate the interaction between neuroscience and happiness based on the advances in Artificial Intelligence. METHODS: A bibliometric analysis was performed with articles from the Scopus database in 2013-2023; likewise, the VOSviewer was used for information processing. RESULTS A total of 603 articles were obtained, and it is evident that the most significant scientific production is centered in the United States (184), United Kingdom (74), and China (73). Three clusters are generated from the Co-occurrence - Author Keywords analysis. The first cluster, red, is related to Artificial Intelligence applications for predicting happiness; the second cluster, green, is associated with Artificial Intelligence tools in neuroscience; and the third cluster, blue, is related to neuroscience in psychology. CONCLUSION: Neuroscience research has made significant leaps in understanding mental processes such as emotions and consciousness. Neuroscience has encountered happiness and is opening up to an approach that seeks evidence to understand people's well-being supported by Artificial Intelligence.

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Transformation and digital challenges in Peru during the COVID-19 pandemic, in the educational sector between 2020 and 2023: Systematic Review

Cited by 2 publications

References 45 publications

Design and Psychometric Properties of the Student Perception of Teacher Care Scale in University Students

Design and Psychometric Properties of the Student Perception of Teacher Care Scale in University Students

Interaction between neuroscience and happiness: assessment from Artificial Intelligence advances

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