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Contradictions and Governance of Student Evaluation of Teaching in Ideological and Political Theory Courses in Universities
CUI Shumin;Student evaluation of teaching is crucial for ensuring the quality of ideological and political theory courses and motivating teachers. However, its actual effectiveness significantly deviates from theoretical expectations, resulting in practical dilemmas such as teacher resistance, student perfunctoriness, and administrative inefficiency. The intertwined contradictions between teacher professionalism and student experientialism, knowledge impartation and value guidance, technical rationality and humanistic care, and managerialism and developmentalism hinder functions of student evaluation of teaching. To resolve these issues, systematic governance centered on concept reshaping,standard reconstruction, technology empowerment, and institutional support is essential, which will ultimately empower teacher growth and enhance educational quality.
Quality and Balanced Supervision and Evaluation of Compulsory Education under System Thinking
ZHANG Hui;System methodology emphasizes understanding complex phenomena from a holistic perspective by grasping their structure, hierarchy, and operational mechanisms, thereby explaining how structure generates function and how function, in turn, reshapes structure. Applying this methodology to realize quality and balanced supervision and evaluation of compulsory education enables the process to be conceptualized as an open system composed of a self-regulatory system, an object system, and an implementation system. In this way, institutional arrangements, operational mechanisms, and procedural processes can be systematically coordinated through a “structure-function” mode, pooling the efforts of multiple stakeholders. This system-oriented approach enhances the relevance, guiding capacity, and improvement-oriented function of supervision and evaluation. It serves as an effective pathway for advancing the quality and balanced supervision and evaluation of compulsory education.
Ethical Governance and Ecological Reconstruction:A Paradigm for Digital Transformation of Educational Evaluation
LI Song;The digital transformation of educational evaluation leverages AI and big data to achieve intelligent and precise evaluation, yet it also faces ethical dilemmas such as algorithmic bias,the dissolution of human agency, and digital alienation. The transformation paradigm of “ethical governance + ecological reconstruction” integrates ethical and ecological elements, establishes a dynamic collaborative closed-loop system, and clarifies the rights and responsibilities of diverse stakeholders. It fosters governance synergy through three mechanisms, i. e., shared objectives,complementary strategies, and mutual evaluation feedback. The ethical governance dimension formulates strategies across four areas, i. e., organization review and standard setting, algorithmic oversight, data privacy safeguards, and digital divide mitigation. The ecological reconstruction dimension focuses on the precise transformation and dynamic adaptation of education-oriented approaches, the deep integration of human-machine collaboration and diversified evaluation, the innovation of government-led and multi-stakeholder collaborative governance, and the cultivation of an ecosystem that fosters continuous innovation.
Research on Teaching Evaluation Strategies in the Context of Generative Artificial Intelligence
JIA Handi;CAI Minjun;Generative artificial intelligence(GenAI) is driving the transformation of teaching evaluation from traditional modes towards human-machine collaboration ecosystem. Teaching evaluation in the GenAI era must first pivot toward competency development, focusing on “21 st-century skills” such as critical thinking and AI prompt refinement. This paper then proposes addressing assignment homogenization by innovating assignment formats, establishing AI usage annotation reflection mechanisms, strengthening AI-free detection, and introducing peer evaluation. Furthermore, a multidimensional formative evaluation system must be developed based on three scenarios, i.e., non-AI use, AI-assisted tasks, and AI-mandated assignments, which incorporates both traditional metrics and new indicators like AI collaboration effectiveness and ethical standards. Guidance on AI ethics and academic integrity must be reinforced.
Paradigm Reconstruction of Engineering Education Assessment in the Age of Digital Intelligence
YI Yingqiu;The advent of the digital-intelligence era introduces new imperatives for the reform of engineering education assessment. Current assessment still exhibits significant shortcomings, for example, its orientation emphasizes “adaptation” over innovation, its methods prioritize summative assessment over process-oriented empowerment, assessment subject is singular, and its methods fall into the trap of “data quantification” without value guidance. To advance paradigm reconstruction, a novel assessment paradigm centered on “creation” should be constructed. Theoretically, this involves cultivation of the “creative subject” as its axiological foundation, adopting “fusion of horizons” as the core mechanism for catalyzing creation, and repositioning digital-intelligent technologies as “enablers”.Operationally, it requires the systematic design of a five-dimensional assessment system integrating objectives, content, evidence, relationships, and technology, and the implementation of key methods such as the “evidence portfolio” and “growth profile”. In terms of implementation, a promotion pathway should be planned, encompassing the redesign of micro-level teaching processes, meso-level organizational and faculty support, and macro-level policy-ecosystem synergy.
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