The study, led by Shahzad Haider of the School Education Department in Lasbela, Balochistan, together with colleagues from institutions across Sindh and Lahore, was designed as a qualitative descriptive investigation rooted in an interpretivist paradigm. Rather than measuring competence through standardized tests or administrative metrics, the researchers wanted to understand the phenomenon through the eyes of the people who live it daily. Ten university teachers were selected using criterion-based purposive sampling, a technique that deliberately recruits participants who possess direct, relevant experience of the issue under investigation. Semi-structured interviews formed the backbone of the data collection, allowing participants to speak at length while the interviewers gently steered the conversation toward the study’s core concerns.

Once the interviews were transcribed, the team turned to an inductive, codebook-informed thematic analysis—a method that lets patterns emerge from the data itself rather than forcing responses into predetermined categories. The analysis converged on a single overarching theme: professional factors shaping professional competence. Beneath that umbrella, five interrelated subthemes surfaced, each representing a distinct strand of the teachers’ understanding: professional attitude, professional development, ICT proficiency, research competence, and change management. Together, these five strands form what the authors describe as a situated and multidimensional form of practice, one that cannot be divorced from the institutional conditions in which it unfolds.

The first strand, professional attitude, speaks to the ethical and dispositional heart of teaching. Participants framed competence not merely as knowing one’s subject but as embodying a commitment to students, to integrity, and to the responsibilities of the profession itself. This aligns with a long tradition in the competence literature, which has repeatedly distinguished between technical skill and the moral orientation that gives that skill meaning. In the Balochistan context, where public universities operate under significant resource pressures, the teachers suggested that attitude functions as a kind of internal compass—sustaining professional behavior even when external incentives and support structures fall short.

Professional development emerged as the second pillar, and here the findings carry a pointed institutional message. The teachers described continuous learning as essential to staying effective, yet they also pointed to uneven access to structured development opportunities across the province’s public universities. The study situates this within a broader Pakistani debate: earlier research has documented how professional development programs can enhance university teachers’ knowledge, but also how provision remains inconsistent. The Balochistan participants’ accounts suggest that where formal programs are scarce, competence becomes something teachers must actively construct for themselves—through reading, peer exchange, and self-directed experimentation with new methods.

Perhaps the most contemporary of the five subthemes is ICT proficiency. The teachers identified digital readiness as an increasingly non-negotiable dimension of professional competence, shaped by the global transformation of higher education and the growing expectation that faculty can navigate learning platforms, digital resources, and technology-mediated pedagogy. This finding echoes international work linking digital competence to teachers’ conceptions of teaching, as well as recent Pakistani studies examining readiness for technology-rich approaches such as STEM education. In Balochistan, however, the researchers note that digital infrastructure itself is unevenly distributed, meaning that a teacher’s ICT proficiency is partly a function of institutional investment rather than individual effort alone.

Research competence formed the fourth strand, reflecting the dual mandate of modern universities: teaching and knowledge production. Participants described scholarly engagement—publishing, conducting studies, staying current with their disciplines—as integral to their professional identity and to the quality of their classroom work. Yet the study highlights that research support in the region’s public universities is limited, creating a gap between the expectations placed on faculty and the resources available to meet them. The teachers’ perspectives suggest that research competence is not simply an individual attribute but a capacity that institutions either nurture or neglect, with consequences for both academic output and student learning.

The fifth subtheme, change management, captures the adaptive dimension of competence. Universities everywhere are being reshaped by technological disruption, evolving student expectations, and shifting policy landscapes, and Balochistan’s public universities are no exception. The teachers in the study described adaptability—the ability to respond constructively to institutional and technological change—as a defining feature of professional competence. This reframes competence as inherently dynamic: what counted as a competent lecturer a decade ago may fall short today, and the professional teacher is one who can read the winds of change and adjust practice accordingly.

The authors are careful about the limits of their work. Because the study is qualitative and interpretive, it cannot establish causal relationships between any particular factor and measured teaching outcomes. What it offers instead is a rich interpretation of how teachers in a specific context make sense of competence—a contribution the researchers argue is overdue, given how little higher education research has focused on Balochistan. The methodological transparency, from the ethics approvals granted by institutional review boards to the written informed consent obtained from all participants before any interviews were recorded, underscores the rigor behind the findings. The authors also declare no competing interests and note that the study received no external funding.

The practical implications, however, are clear and actionable. The study recommends that institutions provide structured professional development, invest in research and ICT capacity building, and cultivate reflective leadership to strengthen professional competence across public universities. In effect, the researchers argue that competence is a shared project: teachers bring attitude and adaptability, but universities must supply the scaffolding—training, infrastructure, and research support—that allows those qualities to flourish. For policymakers in Pakistan and for higher education leaders in similarly under-resourced regions worldwide, the message is that investing in faculty capability is not a luxury but a precondition for institutional quality. As digital transformation accelerates and expectations on universities multiply, the Balochistan study reminds us that the question of what makes a teacher competent is ultimately a question about the systems we build around them—and whether those systems are designed to help educators grow, or left to let them improvise alone.

Subject of Research: University teachers' perceptions of professional factors influencing professional competence in public universities of Balochistan, Pakistan

Article Title: University teachers’ perspectives on professional factors influencing professional competence: a qualitative study in public universities of Balochistan, Pakistan

Article References: Haider, S., Ahmed, S. T., Imran, M., Oad, L., Shaikh, N., & Yaqoob, N. (2026). University teachers’ perspectives on professional factors influencing professional competence: a qualitative study in public universities of Balochistan, Pakistan. SN Social Sciences, 6(10), Article 465. https://doi.org/10.1007/s43545-026-01752-7

Image Credits: AI Generated

DOI: 10.1007/s43545-026-01752-7

Keywords: professional competence, university teachers, professional development, ICT proficiency, research competence, change management, Balochistan, Pakistan, higher education, qualitative study, teacher attitudes, public universities

The research team, led by Firew Bekele Ejigu with colleagues Tariku Sime Gutu and Wudu Melese Tarekegne, surveyed 342 primary school teachers selected through stratified random sampling across the city, complementing the questionnaire data with in-depth interviews and school observations involving six purposively chosen participants. The study employed an embedded mixed-methods design, giving greater weight to the quantitative strand while using qualitative data to contextualize and enrich the statistical findings. Addis Ababa, home to roughly 5.46 million people and often described as a microcosm of Ethiopia, provided an ideal setting: the city’s population includes ethnic Amhara (47 percent), Oromo (19.5 percent), Gurage (16.3 percent), Tigray (6.2 percent) and numerous other groups, alongside Orthodox Christian, Muslim and other religious communities.

The theoretical backbone of the study draws on James A. Banks’s influential framework of multicultural education, which identifies five interlocking dimensions: content integration, the knowledge construction process, equity pedagogy, prejudice reduction, and an empowering school culture. Crucially, Banks’s model insists that multicultural education is not merely a matter of revising textbooks or adding festival days to the calendar. It demands a transformation in teachers’ beliefs, attitudes and everyday instructional practices, because even the most carefully designed curriculum is only as effective as the educator who enacts it in the classroom.

Measuring attitudes required a purpose-built instrument. The researchers constructed a 20-item Likert-type questionnaire ranging from strongly disagree to strongly agree, with negatively worded items reverse-coded during analysis. One sample item probed a common anxiety: whether addressing student diversity in class is dangerous for national unity. Before deployment, the scale was vetted by language instructors and diversity education researchers, then piloted with 15 teachers outside the main sample. The resulting Cronbach’s alpha of 0.754 indicated acceptable internal consistency, and skewness and kurtosis statistics confirmed the scores were approximately normally distributed, clearing the way for parametric testing.

The headline quantitative result was a grand mean score of 3.41 on the five-point scale, with a standard deviation of 1.33. That figure places teachers squarely in the moderate range: above the scale’s midpoint, signaling generally favorable orientations toward weaving diversity into curriculum experiences, but far from uniformly enthusiastic. The variability matters. Some teachers expressed genuine comfort with multicultural content, while others reported discomfort or uncertainty, and the interviews revealed why the average conceals a spectrum of understanding.

Those qualitative conversations were revealing. One teacher described a school where children speak Welayitegna, Afan Oromo, Amharic, Tigrigna and other languages, and where she regularly coordinates cultural shows and Nation and Nationalities Day events. Another participant, a school principal, painted a more cautious picture, noting that while some teachers hold positive attitudes, others avoid discussing diversity openly for fear of being perceived as politically motivated. Several teachers conflated multicultural education with inclusive education for students with disabilities, or equated it narrowly with religion-free schooling, suggesting that conceptual clarity remains a work in progress even among committed educators.

The inferential statistics told a story about what does and does not predict these attitudes. Gender made no significant difference, with male teachers averaging 3.39 and female teachers 3.47, a gap that failed to reach statistical significance. Academic qualification likewise showed no significant relationship, despite degree holders posting the highest raw mean of 3.73. More surprising was the weak, non-significant correlation between the number of languages teachers spoke and their multicultural attitudes, a finding the authors interpret through the lens of how languages are acquired: community-based, everyday multilingualism may matter more than a simple count of languages known.

What did matter was training and career stage. Teachers who had completed multicultural coursework or professional development scored significantly higher, at 3.54 versus 3.34 for those without such exposure, a difference the researchers report as statistically significant. One-way ANOVA results further showed that younger teachers, aged 22 to 35, and those with one to ten years of experience held significantly stronger multicultural attitudes than their older, more seasoned colleagues. The authors caution against attributing this generational pattern to training alone, since the data did not capture when or where teachers studied; generational socialization around diversity values, or younger teachers’ closer cultural proximity to their students, could also play roles. Still, the pattern echoes findings from Norway’s TALIS data, where professional development emerged as a significant predictor of multicultural teaching self-efficacy.

The study’s most sobering statistic may be that 50.6 percent of participating teachers had never received any training in multicultural education. That gap mirrors a continental pattern. Comparable studies in Nigeria, South Africa and Tanzania have documented a recurring attitude-practice divide, in which teachers express rhetorical commitment to cultural diversity but lack the preparation, resources and institutional support to translate that commitment into classroom practice. The Ethiopian findings thus reinforce a growing scholarly consensus that the weakest links across African education systems are content integration, equity pedagogy and empowering school culture, precisely the dimensions that require deliberate, structured intervention.

The implications reach well beyond Addis Ababa. The researchers recommend embedding multicultural education as a core component of teacher preparation, both through dedicated standalone courses and through infusion across subject-specific methods training, alongside continuous in-service workshops and experience-sharing programs. They also call for systematic textbook analysis against Ethiopia’s new Education Sector Development Roadmap and curriculum framework. Because children begin forming evaluative categories about social difference at remarkably early ages, and because teachers serve as the role models from whom young learners internalize attitudes toward out-groups, the stakes of this professional development extend far beyond individual classrooms. In a nation whose founding educational aspiration is unity within diversity, the study suggests that the surest investment is not in policy documents but in the minds of the teachers who open them every morning.

Subject of Research: Primary school teachers' attitudes toward multicultural curriculum integration in Addis Ababa, Ethiopia

Article Title: Primary school teachers’ attitudes towards integrating multiculturalism into curriculum implementation in Addis Ababa city, Ethiopia

Article References: Ejigu, F. B., Gutu, T. S., & Tarekegne, W. M. (2026). Primary school teachers’ attitudes towards integrating multiculturalism into curriculum implementation in Addis Ababa city, Ethiopia. Discover Education, 5(1), Article 1073. https://doi.org/10.1007/s44217-026-02166-6

Image Credits: AI Generated

DOI: 10.1007/s44217-026-02166-6

Keywords: multicultural education, teacher attitudes, Ethiopia, Addis Ababa, primary education, curriculum implementation, professional development, teacher training, cultural diversity, inclusive education, James A. Banks, mixed methods

The study was conducted by Vassilis A. Failadis, Sotiris K. Tasoulis, Spiros V. Georgakopoulos, and Vassilis P. Plagianakos of the University of Thessaly in Greece, and appeared online on September 11, 2026. Rather than surveying the sprawling field of artificial intelligence in education at large, the authors deliberately narrowed their focus to lesson planning, an essential component of a teacher’s daily workload and a core element of professional preparation. Following the search-appraisal-synthesis-analysis framework, known as SALSA, the researchers examined 53 recent publications and organized their findings around four themes: the quality and pedagogical value of AI-generated plans, the challenges and limitations of the technology, teachers’ attitudes and perceptions, and possible improvements and future directions. This focused lens matters, because lesson planning sits at the intersection of content knowledge, curriculum requirements, classroom context, and student needs, making it a revealing test case for what generative models can and cannot do.

The technical verdict on output quality is nuanced. Across the reviewed studies, large language models are frequently praised for producing well-organized plans with clear instructional formats. Platforms such as ChatGPT can reliably follow common instructional models, arranging activities into recognizable stages such as brainstorming, group discussion, guided exploration, presentation, and evaluation. In structural terms, the models have absorbed the conventions of lesson design from their training data and reproduce them fluently. Yet the empirical evidence consistently shows that these plans provide only a general framework and require substantial adaptation before they can function in a real classroom. The plans look like lessons; they do not yet behave like lessons, because they lack the embedded awareness of particular students, curricula, and teaching conditions that experienced educators bring to every plan they write.

Four recurring limitations emerge from the literature with striking consistency. The first is limited pedagogical depth: the teaching practices suggested by large language models tend to promote procedural knowledge rather than conceptual understanding, offering little support for complex learning processes such as reasoning, reflection, and justification. The second is weak differentiation, since the plans rarely include strategies for individualization or alternatives for students with different learning profiles, a shortcoming that becomes especially pronounced in specialized contexts such as special education. The third is unrealistic time planning. One study found that a plan designed by an AI for a single hour would require at least three hours in practice, with the models assigning very short durations to essential tasks while allocating generous time to reminder stages. The fourth is inconsistent output quality, with high variance reported even within identical prompt groups; outputs generated from the same prompt were found to differ by at least five rubric elements, a level of variability that undermines reliability in any professional workflow.

These findings lead the authors to an important practical conclusion about how teachers should interact with the technology. Producing a usable plan from a large language model is not a one-step process but an iterative one, in which the quality of the generated material depends partly on the clarity and specificity of the prompts. This reframes lesson planning with AI as a skill in its own right, blending prompt engineering with pedagogical expertise. A vague request yields a generic skeleton; a precise, context-rich prompt can yield something considerably more useful. But even the best outputs remain drafts that demand professional refinement, because no prompt can fully encode the tacit knowledge a teacher accumulates about how a particular class learns, stalls, and responds.

The review also paints a detailed picture of how teachers themselves perceive these tools. Most educators acknowledge the usefulness of artificial intelligence in lesson planning while simultaneously expressing reservations about its pedagogical adequacy. Teachers commonly use AI to generate content, yet many still prefer to work collaboratively with colleagues and emphasize the need for clear institutional policies to regulate its use. Some see the models as a helpful aid but do not believe they can replace a teacher’s pedagogical judgment; many agree that AI can assist with the initial organization of a lesson while stressing that the final responsibility for adapting and applying the plan lies with the teacher. Intriguingly, the authors observed a generational divide: younger educators tend to be more open to using AI, while more experienced teachers remain cautious, a difference the researchers attribute to the influence of professional experience and familiarity with classroom practice on teachers’ perspectives.

To move the field forward, the review identifies four main directions that appear repeatedly in the literature. The first is teacher training and AI literacy, ensuring that educators understand what these systems can actually do and develop the ability to adapt and assess the content they produce. The second is prompt engineering and reflective use, since the pedagogical value of generated content depends directly on how clear, precise, and well-targeted the prompts are. The third is policy development and ethical guidelines, with clear rules needed to guarantee responsible and educationally appropriate deployment of AI tools in schools. The fourth is model improvement and pedagogical alignment, calling for enhanced features and greater flexibility in instructional design, including guided interfaces and options that allow teachers to supply contextual information about their students, curriculum, and constraints. Together, these directions sketch a roadmap in which the technology and the profession evolve in tandem rather than in competition.

The review is equally candid about what the research itself still does not know, identifying four significant gaps. Most existing studies remain theoretical or rely on teachers’ opinions without examining what happens when AI-generated plans are actually applied in classrooms. Most are built on qualitative observations, interviews, or questionnaires, with limited direct comparisons between teacher-created and machine-generated plans. The literature is also geographically concentrated, with the United States and Türkiye appearing most frequently, raising questions about how findings transfer to other educational systems. Finally, little attention has been paid to the processes through which teachers interact with AI systems during planning, leaving the human-machine workflow largely unexplored. Recent empirical work nonetheless offers telling hints: one study found that although teacher-created plans were rated higher in quality overall, teachers were unable to reliably distinguish them from AI-generated ones, while another found that refined AI-generated mathematics lesson plans received high evaluation scores and in several cases outperformed teacher-created plans, even though teacher-generated procedures aligned more closely with actual classroom practice. The gap between perceived and actual quality is clearly a live scientific puzzle.

The overall conclusion is measured rather than sensational. Large language models can serve as useful tools for lesson planning, but they are not yet capable of replacing the teacher’s pedagogical role. Their outputs are usually well-structured, organized, and goal-oriented, yet they tend to fall short in adaptation, differentiation, and pedagogy, the dimensions that determine whether a plan actually teaches anyone anything. As the authors put it, these systems should currently be viewed as support for lesson planning rather than as ready-made planning tools, and should not yet be considered a substitute for pedagogical expertise; their use makes sense when they function as support tools rather than as replacements for professional judgment. For a technology often portrayed as poised to automate teaching outright, the evidence points to a more grounded future: AI as a fast, tireless drafting assistant, and the teacher as the indispensable editor who knows exactly which students are sitting in the room.

Subject of Research: The use of large language models for lesson planning in education and their pedagogical limitations

Article Title: Large language models in lesson planning: Useful aid, but not yet ready to replace teachers

Article References: Large language models in lesson planning: Useful aid, but not yet ready to replace teachers. (n.d.). Original publication

Image Credits: AI Generated

DOI: Not provided

Keywords: large language models, lesson planning, generative AI, ChatGPT, education technology, pedagogy, teacher attitudes, prompt engineering, AI literacy, narrative review, differentiation, Frontiers of Digital Education