The rapid advancement of artificial intelligence (AI) has outpaced existing research and regulatory frameworks in higher education, leading to varied institutional responses. Although some educators and institutions have embraced AI and generative AI (GenAI), other individuals remain cautious. This systematic literature review explored teaching academics' attitudes, perceptions and intentions towards AI and GenAI, identifying perceived benefits and obstacles. Utilising the unified theory of acceptance and use of technology framework, this study reveals positive attitudes towards AI's efficiency and teaching enhancement, but also significant concerns about academic integrity, accuracy, reliability, skill development and the need for comprehensive training and policies. These findings underscore the necessity for institutional support to navigate the integration of AI and GenAI in tertiary education. Implications for practice or policy: Attitudes towards AI and GenAI integration are diverse with educators recognising benefits but raising ethical and practical concerns. These concerns indicate a need for a more comprehensive understanding and dialogue within academic communities. Academics' intentions to use these technologies are contingent upon the development of robust ethical guidelines and supportive institutional policies. Institutional support and training shape behaviours. The scarcity of formal training, systematic guidelines and policy frameworks currently limits effective integration.

The laboratory is an integral component of engineering education, resulting in a multitude of studies. Generally, the research focus is on the laboratory innovation, rather than learning itself. It is observed that empirical evidence is strongly built around student perceptions of their learning or experience via survey instruments; and in some cases, complimented with limited quantitative measures including assessments. With the laboratory being a multifaceted, multi-domain learning environment also covering the psychomotor and affective domains, such observations suggest that the empirical data being collected is providing an incomplete analysis. Therefore, this paper undertakes a systematic literature review exploring remote, simulation and traditional laboratory studies that explicitly include assessment analysis. Explored are the types of assessments used and assessment innovations. The study 1) confirms that assessments concentrate on the cognitive domain, underselling the learning being achieved; 2) Student survey instruments play an important role in measuring laboratory success; 3) Background information of the learning objectives are not clearly stated and/or not clearly linked to the associated assessment; 4) There are several research opportunities available to improve understanding of laboratory assessments. A roadmap and recommendations to overcome these weaknesses is outlined, providing a platform for future researchers to incorporate in their studies.

Contribution: This article provides evidence that perceived learning has a relationship and influences the way students evaluate laboratory experiments, facilities, and demonstrators. Background: Debate continues on the capability and/or reliability of students to evaluate teaching and/or learning. Understanding such relationships can help educators decode evaluation data to develop more effective teaching experiences. Research Question: Does a relationship exist between student evaluation scores and perceived learning? Methodology: Perceived learning across the cognitive, psychomotor, and affective domains was measured using the Laboratory Learning Objectives Measurement (LLOM) tool at an Australian (344 students) and Serbian (181 students) university. A multilevel statistical analysis was conducted. Findings: Statistically significant relationships were found between student evaluation scores and perceived learning across the cognitive, psychomotor, and affective domains with some differences found between the two universities. This provides evidence that perceived learning plays a role in influencing student evaluation scores. Students perceived an improvement of learning across all three domains confirming the multifaceted benefits of the laboratory for engineering education.