Publicación:
Plithogenic Statistical Analysis of Teaching Performance in Student Autonomous Learning

dc.contributor.authorChávez, Felipe Aguirre
dc.contributor.authorSolorzano, Rolando Oscco
dc.contributor.authorSoto Zedano, Freddy Alejandro
dc.contributor.authorOscco Solorzano, María Eva
dc.contributor.authorQuivio Cuno, Richard Santiago
dc.contributor.authorSaico, Delio Merma
dc.date.accessioned2025-08-15T15:28:49Z
dc.date.issued2024
dc.description.abstractIn the current educational context, the effectiveness of teaching performance in blended environments has acquired significant relevance. The present research focused on evaluating the relationship between professional teaching competencies and the achievement of student competencies in the blended context. To this end, perceptions of teacher performance and instrumental, interpersonal, and systemic competencies were evaluated using plithogenic statistics. Among the results, they indicated that the student's perception of teaching performance in relation to classroom management and professional development was positive. However, areas of improvement were identified in interpersonal and technical skills. Observations suggest that teacher performance significantly influences the achievement of student competencies. Consequently, it has been concluded that continuing training programs must be developed for future pedagogical interventions and curricular adjustments in blended environments. © 2024, University of New Mexico. All rights reserved.
dc.identifier.scopus2-s2.0-85218856362
dc.identifier.urihttps://cris.une.edu.pe/handle/001/755
dc.identifier.uuidfc152b02-6e6a-4789-8773-6c603acd55c0
dc.language.isoen
dc.publisherUniversity of New Mexico
dc.relation.citationvolume71
dc.relation.ispartofNeutrosophic Sets and Systems
dc.rightshttp://purl.org/coar/access_right/c_14cb
dc.subjectblended learning
dc.subjectplithogenic statistics
dc.subjectstudent competencies
dc.subjectteaching performance
dc.titlePlithogenic Statistical Analysis of Teaching Performance in Student Autonomous Learning
dc.typehttp://purl.org/coar/resource_type/c_2df8fbb1
dspace.entity.typePublication
oaire.citation.endPage113
oaire.citation.startPage105

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