In recent years, significant developments have occurred in AI-based chatbots that have been effectively deployed in the educational field. However, given the novelty of this technology, descriptive analyses remain scarce. Although many review studies have focused on the effectiveness of chatbots, they generally present broad results, and only a few have addressed the impact of this technology on learning outcomes. The present study examines the educational implications of AI chatbots on various learning outcomes through a post hoc analysis conducted in accordance with PRISMA principles. It aims to aggregate and analyze findings from studies that examined the use of chatbots and their impact on specific learning outcomes. A total of 26 studies were selected from a pool of 6,721 published between 2021 and 2024 and indexed in the Scopus and Web of Science databases. Data analysis was conducted using the Newcastle-Ottawa Scale (NOS) for Education. The results revealed that AI-chatbot technology has a positive influence on several learning outcomes, including academic achievement, motivation, self-assessment, engagement in learning, self-efficacy, and language learning, among others. The studies also detailed the methodologies and tools employed in these investigations. The study also offers insights into how intelligent chatbots can be leveraged to enhance various learning outcomes.

The introduction of evolution in post-apartheid South Africa in 2008 presented significant challenges for teachers, due to both their own and their students' faith-based biases. This study investigates South African teachers' attitudes and understanding of evolution, utilizing Lemkian sociocultural theory and Vygotskian ZPD scaffolding. A mixed-methods approach was employed, including a Likert-scale questionnaire from 91 life science teachers and qualitative insights from open-ended questions. Results reveal a lack of enthusiasm for teaching evolution, influenced by personal religious beliefs and doubts about its scientific validity. Teachers often call for equal representation of evolution and creationism in classrooms. The preparation of teachers must address the stagnant discussion of evolution, while the life sciences curriculum emphasizes the Nature of Science, scientific literacy, and connections between science and society is compromised.

Binary classifications of teaching as transmission or constructivism obscure how participation, authority, knowledge practices, and conceptual work can vary within one lesson. This article introduces the social, procedural, epistemic, and conceptual (SPEC) framework for episode-level lesson analysis. SPEC was developed through a structured purposive theory synthesis rather than an exhaustive systematic review. A documented corpus of foundational traditions, observation systems, and targeted verification sources was compared using explicit inclusion, boundary, and disposition rules. Candidate constructs were assigned by observable target; three indicators per dimension were retained as a parsimonious authorial proposal; and qualitative descriptors were generated from theoretically warranted adjacent distinctions checked against cross-dimensional counterexamples. The dimensions are analytically distinguishable but potentially related. Their descriptor codes form non-additive, non-normative profiles rather than composite scores or judgments of teaching quality. An instructional episode is the primary unit; a hypothetical transcript illustrates indicator coding, opportunity/evidence flags, and rejection of nearby alternatives. SPEC is an initial conceptual proposal requiring operationalization, reliability examination, and validity testing. Ordering, thresholds, and cross-domain use require study before evaluative application.