2022 Open Access Fund Recipients
http://hdl.handle.net/10464/16527
2024-03-28T11:39:28ZPower research in adaptive water governance and beyond: a review
http://hdl.handle.net/10464/17857
Power research in adaptive water governance and beyond: a review
McIlwain, Lisa; Holzer, Jennifer; Baird, Julia; Baldwin, Claudia
Power dynamics are widely recognized as key contributors to poor outcomes of environmental governance broadly and specifically for adaptive water governance. Water governance processes are shifting, with increased emphasis on collaboration and learning. Understanding how power dynamics impact these processes in adaptive governance is hence critical to improve governance outcomes. Power dynamics in the context of adaptive water governance are complex and highly variable and so are power theories that offer potential explanations for poor governance outcomes. This study aimed to build an understanding of the use of power theory in water and environmental governance and establish a foundation for future research by identifying power foci and variables that are used by researchers in this regard. We conducted a systematic literature review using the Web of Science Core Collection and the ProQuest Political Science databases to understand how power is studied (foci, variables of interest, and methods) and which theories are being applied in the water governance field and in the environmental governance field more broadly. The resulting review can serve as a practical reference for (adaptive) water governance inquiries that seek to study power in depth or intend to integrate power considerations into their research. The identified power variables add to a much needed groundwork for research that investigates the role of power dynamics in collaboration and learning processes. Furthermore, they offer a substantive base for empirical research on power dynamics in adaptive water governance.
2023-01-01T00:00:00ZFaculty members’ use of artificial intelligence to grade student papers: a case of implications
http://hdl.handle.net/10464/17810
Faculty members’ use of artificial intelligence to grade student papers: a case of implications
Kumar, Rahul
This paper presents the case of an adjunct university professor to illustrate the dilemma of using artificial intelligence (AI) technology to grade student papers. The hypothetical case discusses the benefits of using a commercial AI service to grade student papers—including discretion, convenience, pedagogical merits of consistent feedback for students, and advances made in the field that yield high-quality work—all of which are achieved quickly. Arguments against using AI to grade student papers involve cost, privacy, legality, and ethics. The paper discusses career implications for faculty members in both situations and concludes with implications for researchers within the discourse on academic integrity.
2023-05-15T00:00:00ZPreservice teachers’ science learning and self-efficacy to teach with robotics-based activities: Investigating a scaffolded and a self-guided approach
http://hdl.handle.net/10464/17659
Preservice teachers’ science learning and self-efficacy to teach with robotics-based activities: Investigating a scaffolded and a self-guided approach
Jaipal-Jamani, Kamini
Introduction: Robotics is viewed as a viable pedagogical strategy for STEM learning because it is characterized by many practices common to the STEM disciplines such as engineering design. With many national curricular calling for STEM integration in K-12 formal educational settings, there is a need for empirical evidence about the effectiveness of different pedagogical approaches to teach with robotics-based activities to promote curriculum learning outcomes and teaching practice. This exploratory study investigated the effectiveness of a scaffolded robotics intervention and a self-guided robotics intervention on pre-service teacher knowledge (PST) of science concepts related to gears and on PST self-efficacy to teach with the robotics-based activities.
Methods: A quasi-experimental, pre-post intervention study was implemented with two non-equivalent groups of elementary preservice teachers (PSTs) in a Bachelor of Education program. PSTs in the self-guided group (n = 11) worked with robotics kits in the library at their own pace. PSTs in the scaffolded intervention group (n = 16) were guided through the activity by the author with instructional scaffolds. IBM SPSS Statistics 27 was used to analyze the data.
Results: The relationship between intervention type and gains in science knowledge was not statistically significant for the self-guided group but was statistically significant for the scaffolded group suggesting that scaffolding supported PST’s learning of the science concepts. With respect to PST self- efficacy to teach with the robotics-based activity, both intervention types revealed statistically significant gains from pre to post tests, however effect sizes indicated that the scaffolded intervention resulted in greater gains in PST self-efficacy to teach with the robotics-based activities.
Discussion: The results provide exploratory evidence that the scaffolded robotics approach, modelled for and experienced by the pre-service teachers in this study, was effective for their learning of science curricular concepts related to gears and for developing their self-efficacy for teaching the robotics-based activities. It should be noted that findings may not be generalizable due to the small sample sizes, especially of the self-guided group. Nevertheless, the findings do provide insights for teacher educators incorporating robotics-based activities into curricular courses such as science methods as it provides specific examples of scaffolds that were effective for science learning and for developing PST self-efficacy. The study also contributes to the literature on instructional strategies that promote robotics adoption in K-12 schools to support development of STEM knowledge and skills.
2023-03-16T00:00:00ZChronic AMPK Activation Reduces the Expression and Alters Distribution of Synaptic Proteins in Neuronal SH-SY5Y Cells.
http://hdl.handle.net/10464/17658
Chronic AMPK Activation Reduces the Expression and Alters Distribution of Synaptic Proteins in Neuronal SH-SY5Y Cells.
Yang, Alex J T; Mohammad, Ahmad; Tsiani, Evangelia; Necakov, Aleksandar; MacPherson, Rebecca E K
Neuronal growth and synaptic function are dependent on precise protein production and turnover at the synapse. AMPK-activated protein kinase (AMPK) represents a metabolic node involved in energy sensing and in regulating synaptic protein homeostasis. However, there is ambiguity surrounding the role of AMPK in regulating neuronal growth and health. This study examined the effect of chronic AMPK activation on markers of synaptic function and growth. Retinoic- acid-differentiated SH-SY5Y human neuroblastoma cells were treated with A-769662 (100 nM) or Compound C (30 nM) for 1, 3, or 5 days before AMPK, mTORC1, and markers for synapse function were examined. Cell morphology, neuronal marker content, and location were quantified after 5 days of treatment. AMPK phosphorylation was maintained throughout all 5 days of treatment with A-769662 and resulted in chronic mTORC1 inhibition. Lower total, soma, and neuritic neuronal marker contents were observed following 5 d of AMPK activation. Neurite protein abundance and distribution was lower following 5 days of A-769662 treatment. Our data suggest that chronic AMPK activation impacts synaptic protein content and reduces neurite protein abundance and distribution. These results highlight a distinct role that metabolism plays on markers of synapse health and function.
2022-07-31T00:00:00Z