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Pausing behavior in introductory Computer Science (CS1) courses has been related to course outcomes and could be linked to a student’s cognitive load. Using Cognitive Load Theory and Vygotsky’s Zone of Proximal Development as a theoretical framework, this study empirically analyzes keystroke latencies, or pause times between keystrokes, with the goal of better understanding what types of assignments need more scaffolding than others. We report the characteristics of eleven assignments, introduce a method to analyze pausing behavior, and investigate how pausing behavior changes with assignment characteristics (e.g., introducing new programming constructs, engaging creativity through Turtle graphics, etc). We find evidence that pausing behavior does change based on the assignment characteristics and that assignments with particular characteristics, such as object-oriented principles, may be more likely to have excessive demands on student working memory. We also find evidence that assignment completion time may not be an accurate measure of assignment difficulty.
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ASAP: An automatic sequential assignment program for congested multidimensional solid state NMR spectra
Accurate signal assignments can be challenging for congested solid-state NMR (ssNMR) spectra. We describe an automatic sequential assignment program (ASAP) to partially overcome this challenge. ASAP takes three input files: the residue type assignments (RTAs) determined from the better-resolved NCACX spectrum, the full peak list of the NCOCX spectrum, and the protein sequence. It integrates our auto-residue type assignment strategy (ARTIST) with the Monte Carlo simulated annealing (MCSA) algorithm to overcome the hurdle for accurate signal assignments caused by incomplete side-chain resonances and spectral congestion. Combined, ASAP demonstrates robust performance and accelerates signal assignments of large proteins (>200 residues) that lack crystalline order.
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- Award ID(s):
- 1856055
- PAR ID:
- 10522395
- Publisher / Repository:
- Elsevier
- Date Published:
- Journal Name:
- Journal of Magnetic Resonance
- Volume:
- 361
- Issue:
- C
- ISSN:
- 1090-7807
- Page Range / eLocation ID:
- 107664
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1016/j.jmr.2024.107664
