Scholarlink

<p>This study examines how international doctoral students in teacher education conceptualize readiness for Human-Centered Artificial Intelligence (HCAI) and perceive the role of quality assurance (QA) in supporting the ethical integration of AI in higher education. Twenty-five international doctoral students in teacher education returned questionnaires; five who reported not using AI were excluded, as direct engagement with AI was an inclusion criterion, yielding an analytic sample of twenty AI-using educators. Data were analyzed through reflexive thematic analysis following Braun and Clarke’s six-phase approach, with trustworthiness addressed through reflexive journaling, peer debriefing, member reflections, and a documented audit trail. Three themes were constructed. Participants framed HCAI readiness predominantly through relational and ethical capacities: empathy, dialogue, and professional judgment over algorithmic outputs, while technical competence appeared reactively, activated mainly when AI systems failed or produced unreliable outputs. Participants endorsed the shift from episodic audit to adaptive QA but identified an unresolved operational tension between standardization and flexibility. Implementation was described as embedded in institutional ecologies shaped by resource, cultural, and ethical constraints, with systemic-level policy environments largely absent from practitioner narratives. Interpreted against the HCAI Readiness Framework advanced in the paper, these findings suggest three refinements. First, pedagogical and ethical readiness fuse into a relational-ethical composite rather than operating as a symmetrical triad with technical readiness. Second, adaptive QA requires procedural criteria for reconciling standardization with flexibility, rather than merely a normative commitment to flexibility. Third, three-tier governance models may be phenomenologically thin at the systemic register when examined from the practitioner standpoint. Rather than positioning teacher readiness and institutional QA as sequential stages, the analysis theorizes them as reciprocally constitutive conditions requiring concurrent intervention across individual competency, institutional policy, and systemic governance.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

Teacher readiness and adaptive quality assurance for human-centered AI in higher education

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年7月17日

查看全文
  • Balqees Rashid Suleiman AlMandhari,
  • Thet Thet Mar,
  • Mária Hercz,
  • Anisa Trisha Pabingwit

摘要

This study examines how international doctoral students in teacher education conceptualize readiness for Human-Centered Artificial Intelligence (HCAI) and perceive the role of quality assurance (QA) in supporting the ethical integration of AI in higher education. Twenty-five international doctoral students in teacher education returned questionnaires; five who reported not using AI were excluded, as direct engagement with AI was an inclusion criterion, yielding an analytic sample of twenty AI-using educators. Data were analyzed through reflexive thematic analysis following Braun and Clarke’s six-phase approach, with trustworthiness addressed through reflexive journaling, peer debriefing, member reflections, and a documented audit trail. Three themes were constructed. Participants framed HCAI readiness predominantly through relational and ethical capacities: empathy, dialogue, and professional judgment over algorithmic outputs, while technical competence appeared reactively, activated mainly when AI systems failed or produced unreliable outputs. Participants endorsed the shift from episodic audit to adaptive QA but identified an unresolved operational tension between standardization and flexibility. Implementation was described as embedded in institutional ecologies shaped by resource, cultural, and ethical constraints, with systemic-level policy environments largely absent from practitioner narratives. Interpreted against the HCAI Readiness Framework advanced in the paper, these findings suggest three refinements. First, pedagogical and ethical readiness fuse into a relational-ethical composite rather than operating as a symmetrical triad with technical readiness. Second, adaptive QA requires procedural criteria for reconciling standardization with flexibility, rather than merely a normative commitment to flexibility. Third, three-tier governance models may be phenomenologically thin at the systemic register when examined from the practitioner standpoint. Rather than positioning teacher readiness and institutional QA as sequential stages, the analysis theorizes them as reciprocally constitutive conditions requiring concurrent intervention across individual competency, institutional policy, and systemic governance.