Science education

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose "modeldissection" as an alternative to "model-building," whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to "dissect" out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model-based interventions for two cohorts of students, we find that both the "builders" and the "dissectors" improve in the post-test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic timeefficiency of "model dissection," suggest that it could be a valuable pedagogical tool. V

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose "modeldissection" as an alternative to "model-building," whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to "dissect" out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model-based interventions for two cohorts of students, we find that both the "builders" and the "dissectors" improve in the post-test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic timeefficiency of "model dissection," suggest that it could be a valuable pedagogical tool. V

Studies show that people can recognize their own movements, such as their own walking (presented in silhouette using point lights), their own drawing (presented as a moving point light), own clapping, and their own piano playing. We extend this result to proprioceptive control, showing that people can recognize their own eye movements, when presented as just a point moving against a black background. Eye movements were recorded using a wearable eye tracking glass, while participants executed four tasks. A week later, participants were shown these videos, alongside another person's videos, for each task, and asked to recognize their own movements. Males recognized their own eye movements significantly above chance, but only for tasks with large and familiar body movements. Females performed below chance in these tasks. We argue that the standard common coding/motor simulation model does not account for this result, and propose an extension where eye movements and body movements a...

Memes are the packets of information that we acquire by interacting with other people. In a narrow sense, we connect meme with its popular form on social media, where we happily consume, create and transmit it for its humour and/or sarcasm. Given the current pandemic state, when the teaching-learning process has been hit hard with unpredictability, it is apt that novel steps are taken to restore some sense of normalcy and ease students' stress and anxiety. It is both this motivation and the cognisance about the role of memes on digital platforms that a mid-semester exam for a course on human-computer interaction (HCI) was modified to encourage graduate students to give way to their memetic expressions. As part of the exam, 15 graduate students were asked to design five different memes based on their readings and discussions in the HCI course. This activity was followed by a survey to elicit students' understanding about the designing process and to probe their memetic reasoning. In this study, we identify meme-cases to reveal students' perceptions and also share the findings from the survey which suggests that majority of the students-a) enjoyed creating memes for their exam, b) referred to more than four different resources for creating their memes, c) referred to most of the content for the course, and d) did not actively seek feedback for improving their memes. Implications are drawn from the study to use technology and social media to design novel methods to engage students with their learning process.

Critical thinking: Genesis • The progressive-education movement, which was strong in the United States from the 1920's through the 1950's, adopted and developed Dewey's emphasis on reflective thinking. • In Progressive Education Association's monumental "Eight-Year Study," which took place in the 1930's, the words 'critical thinking' and 'clear thinking' replaced 'reflective thinking' (Smith & Tyler, pp. 35-37), and a 1942 yearbook of the National Council for Social Studies used 'critical thinking' in its title, Teaching Critical Thinking in the Social Studies (Anderson, 1942). • Ennis' first published article was about the teaching of critical thinking ('Critical Thinking: More on Its Motivation,' Ennis, 1956). Robert H. Ennis CT may be defined as reasonable reflective thinking that helps one decide what to believe or do (Ennis, 1985) Critical thinking using technological tools • In a review on cultivating critical thinking using e-learning environments and tool, Haghparast et al., (2014) found that these tools are either too time consuming or are too complex. • In a Learning Management System (LMS), interactive components were found to play a significant role in facilitating critical thinking (Saadé, Morin & Thomas, 2012). • 'Socratic' dialogues facilitated during small-group online discussions helped college students in a large university class practice critical thinking (Yang, 2008). • CT skills need to be naturally integrated with the process of learning. This way, the chances of translation of CT skills across domains increases. • Reflection is an essential part of critical thinking. Schön, (2017) suggests that reflective practitioners often engage in reflection while doing a task (reflection-inaction) as well as after doing the task (reflection-on-action).

When students build physical models from prefabricated components to learn about model systems, there is an implicit trade-off between the physical degrees of freedom in building the model and the intensity of instructor supervision needed. Models that are too flexible, permitting multiple possible constructions require greater supervision to ensure focused learning; models that are too constrained require less supervision, but can be constructed mechanically, with little to no conceptual engagement. We propose "modeldissection" as an alternative to "model-building," whereby instructors could make efficient use of supervisory resources, while simultaneously promoting focused learning. We report empirical results from a study conducted with biology undergraduate students, where we demonstrate that asking them to "dissect" out specific conceptual structures from an already built 3D physical model leads to a significant improvement in performance than asking them to build the 3D model from simpler components. Using questionnaires to measure understanding both before and after model-based interventions for two cohorts of students, we find that both the "builders" and the "dissectors" improve in the post-test, but it is the latter group who show statistically significant improvement. These results, in addition to the intrinsic timeefficiency of "model dissection," suggest that it could be a valuable pedagogical tool. V