150 research outputs found
Analysing student problem solving:Successes and challenges
No full textTwo well-known challenges in chemistry education are: developing problem-solving skills by students and teaching of these skills by educators. Extensive chemical education literature deals with the nature of associated difficulties and instructional approaches to address them. One of the main difficulties experienced by students, when solving chemistry problems, stems from the lack of process skills. We have tackled this challenge by developing and evaluating the problem-solving workflow “Goldilocks Help” (Yuriev et al, 2017). It provides specific scaffolding for students faced with procedural difficulties related to solving chemistry problems. The evaluation showed that the workflow helped to shift students’ beliefs about their abilities to use productive self-regulation strategies in problem solving: planning, information management, monitoring, debugging, and evaluation. In fact, analysis of student work showed that many of them could effectively regulate their problem solving though planning and analysis (Yuriev et al, 2019). Furthermore, students who demonstrated structured problem solving and explicit reasoning in their work were more successful in their problem-solving attempts. However, contrary to their stated values, they still found it challenging to monitor, debug, and evaluate effectively. In this presentation, I will use exemplars of student work as well as aggregated analyses to illustrate these findings.We propose that it is important to constructively align teaching and learning activities with assessment that explicitly encourages students to demonstrate their reasoning, and other reflective and evaluative practices, during problem solving
Characteristics of problem solving in spectroscopy: Productive and unproductive pathways
No full textSolving spectroscopy problems is a complex challenge. There are many possible approaches to solving such problems however students often believe there is only a single right pathway to reach the correct endpoint. Previously, we generated teaching resources by recording solutions produced by Honours and PhD students, postdocs, senior researchers, and professors (Yuriev, 2018). This presentation will cover the novel analysis of these recordings, that was carried out to identify productive and unproductive pathways in problem solutions and to explore their novice and expert characteristics. Think-aloud interviews revealed that participants with different academic levels demonstrated common problem-solving features, for example assessing completion. However, the feature expression was expertise-dependent. For example, all participants initiated problem solution by interpreting spectral data, however novices did it less productively than the experts. Similarly, unlike novices, experts were able to explicitly verbalise their problem-solving strategies and reflect on the quality and meaning of the solution outcome. Recognising alternative problem-solving pathways highlights the diverse ways a problem can be interpreted and solved. The multiple possible strategies identified during the analysis will inform spectroscopy teaching and learning and will allow students to develop their own strategies to solving spectroscopy problems.
REFERENCE
Yuriev, E., Burton, J., Vo, K., Maher, S., Thompson, C., & Scanlon, M. (2018). Engaging students with multiple pathways for problem solving. Proceedings of the Australian Conference on Science and Mathematics Education (pp. 104-105). Flinders University, Adelaide, Australia
Editorial: Structural and computational glycobiology – immunity and infection
No full textInterest in understanding the biological role of carbohydrates has increased significantly over the last 20 years. The use of structural techniques to understand carbohydrate-protein recognition is still a relatively young area, but one that is of emerging importance. The high flexibility of carbohydrates significantly complicates the determination of high quality structures of their complexes with proteins. Specialized techniques are often required to understand the complexity of carbohydrate recognition by proteins. In this Research Topic, we will focus on structural and computational approaches to understanding carbohydrate recognition by proteins involved in immunity and infection. Particular areas of focus include cancer immunotherapeutics, carbohydrate-lectin interactions, glycosylation and glycosyltransferases
STUDENT DEVELOPMENT OF PROBLEM-SOLVING SKILLS USING METACOGNITIVE SCAFFOLDING
No full textDespite problem solving being a core skill in chemistry, students struggle to solve chemistry problems. This difficulty may be the result of students trying to solve problems through memorising algorithms. Our research group developed a metacognitive scaffold, known as Goldilocks Help, to support students through structured problem solving and its phases, such as planning and evaluation (Yuriev et al., 2017). This study investigated how first-year chemistry students engaged with the scaffold and how that engagement affected their learning. Data was collected from the assignments, which involved students solving an allocated problem and reflectively comparing their effort to an expert solution. This qualitative study was underpinned by a social constructionist epistemology. A mixed-method approach of frequency and thematic analyses was used. Initially, students did not engage with the scaffold due to viewing it as extra work and time, that needed to be done in addition to solving a problem. Over repeated assignment cycles, students showed greater engagement with the scaffold and became more metacognitively self-aware. Scaffold use and observing the expert solution, helped students to reflect and articulate their problem-solving processes. Students were able to identify improvement strategies and potential points of error that could be avoided.
REFERENCE
Yuriev, E., Naidu, S., Schembri, L., Short, J. (2017). Scaffolding the development of problem-solving skills in chemistry: guiding novice students out of dead ends and false starts. Chemistry Education Research and Practice, 18, 486-504
Student approaches to problem solving: What do students really think when they solve problems?
No full textStudents use multiple strategies to solve chemical problems. However, not all problem-solving approaches are conducive to successful problem solving. The effectiveness of an individual’s approach depends on their content knowledge, experience, and metacognitive skills. In this research project, we explored the pathways students undertake while solving chemical problems by conducting think-aloud interviews with first-year undergraduate students. The interviews were analysed thematically and student problem-solving approaches were categorised into productive or unproductive (Rodriguez et al., 2019; Yuriev et al., 2017). Unsuccessful attempts lacked structure and relied on a trial-and-error approach. For example, these students listed all equations they could recall in an attempt to match to the data found in the problem. Successful students took a more structured and meaningful approach. For example, they identified core concepts underlying the problem in order to apply relevant knowledge. Additionally, successful students readily integrated metacognitive strategies to monitor the productivity of their approach. These techniques allowed them to identify errors and assess whether their answer sounded reasonable. An understanding of the variety of student problem-solving approaches, productive and unproductive, will help to inform instruction that addresses student misconceptions and accounts for student struggles with problem solving.
REFERENCES
Rodriguez J. G., Bain K., Hux N. P. & Towns M. H. (2019). Productive features of problem solving in chemical kinetics: More than just algorithmic manipulation of variables. Chemistry Education Research and Practice, 20, 175-186.
Yuriev, E., Naidu, S., Schembri, L., & Short, J. (2017). Scaffolding the development of problem-solving skills in chemistry: Guiding novice students out of dead ends and false starts. Chemistry Education Research and Practice, 18, 486-504
The development and application of in silico mapping techniques for the study of carbohydrate-protein interactions
No full textCarbohydrate-protein interactions are exquisitely specific, and underpin many biological and biochemical processes. In particular, carbohydrate-antibody recognition is the initial step in transplant rejection across ABO blood group and species barriers. Such interactions are difficult to structurally characterize, due to the high flexibility of carbohydrates. In silico techniques can be used to fill the gaps in structural knowledge, but must be thoroughly validated prior to use. In this project, novel in silico mapping techniques were developed and validated for investigating carbohydrate-protein recognition, with a focus on carbohydrate-antibody recognition. Anti-αGal antibodies, which recognize the αGal epitope on porcine tissues and are involved in the rejection of pig-to-human xenografts, were used as a test system throughout the project. A selection of docking programs were evaluated for their ability to reproduce the carbohydrate binding modes of a series of high resolution carbohydrate-antibody crystal structure complexes. Of the programs investigated, it was found that Glide performed the best at this task. The results also highlighted that interaction-based approaches could be useful in identifying likely binding modes. A “site mapping” technique was developed, which utilizes information from a given docking ensemble to identify protein residues likely to be involved in ligand recognition. The technique was validated for carbohydrate-antibody recognition using poses generated by Glide. Application of the technique to a panel of anti-αGal antibodies established the structurally conserved nature of carbohydrate recognition by these antibodies. Since site mapping alone cannot be used to infer likely binding modes, ligand-based mapping approaches were developed. The “epitope mapping” technique is used to determine ligand atoms likely to be involved in protein interaction. The “conformation mapping” technique is used to identify likely torsion angles of carbohydrate glycosidic linkages. Both of these techniques utilize the same docking ensemble as the site mapping technique. By combining the output from the three mapping techniques, likely carbohydrate binding modes of the anti-αGal antibodies were determined. These binding modes demonstrated the structural basis of the observed carbohydrate selectivity by two of these antibodies. The site mapping technique was applied to investigate peptide-antibody recognition, highlighting its potential application in the design of carbohydrate-mimetic peptides. The technique was validated using a series of high resolution peptide-antibody crystal structure complexes. The recognition of peptide mimics of the αGal epitope by the anti-αGal antibodies was investigated using the site mapping technique. By comparing the carbohydrate- and peptide-derived site maps for each of the antibodies, it was determined that the peptides largely act as structural mimics of the carbohydrates. Carbohydrate-lectin recognition was also investigated using molecular docking and the site mapping technique. Although molecular docking could usually identify the crystal bound carbohydrate conformation, it was rarely ranked highly. This highlights the need for alternative scoring approaches when studying carbohydrate-lectin recognition using molecular docking. Site mapping was shown to identify lectin residues involved in carbohydrate recognition with improved consistency and accuracy over the top ranked docking pose, and thus, mapping techniques may be useful for these structurally investigating these challenging systems. The in silico mapping techniques developed in this project are likely to be generally useful for studying ligand-protein recognition, as well as being valuable tools for drug design.Awards: Winner of the Mollie Holman Doctoral Medal for Excellence, Faculty of Pharmacy and Pharmaceutical Sciences, 2011
A computational approach for exploring carbohydrate recognition by lectins in innate immunity
No full textRecognition of pathogen-associated carbohydrates by a broad range of carbohydrate-binding proteins is central to both adaptive and innate immunity. A large functionally diverse group of mammalian carbohydrate-binding proteins are lectins, which often display calcium-dependent carbohydrate interactions mediated by one or more carbohydrate recognition domains. We report here the application of molecular docking and site mapping to study carbohydrate recognition by several lectins involved in innate immunity or in modulating adaptive immune responses. It was found that molecular docking programs can identify the correct carbohydrate-binding mode, but often have difficulty in ranking it as the best pose. This is largely attributed to the broad and shallow nature of lectin binding sites, and the high flexibility of carbohydrates. Site mapping is very effective at identifying lectin residues involved in carbohydrate recognition, especially with cases that were found to be particularly difficult to characterize via molecular docking. This study highlights the need for alternative strategies to examine carbohydrate-lectin interactions, and specifically demonstrates the potential for mapping methods to extract additional and relevant information from the ensembles of binding poses generated by molecular docking. © 2011 Agostino, Yuriev and Ramsland
SUPPORT FOR PROBLEM SOLVING THROUGH SCAFFOLDING
No full textStudents often have difficulty solving chemistry problems. This difficulty may be compounded by students trying to solve problems by memorised algorithms and/or meaningless manipulation of mathematical operations. To address these challenges, our group developed a scaffold (Goldilocks Help) to support students through structured problem solving and its phases, such as planning and evaluation (Yuriev et al., 2017). This study explored how first-year chemistry students engaged with the problem-solving scaffold and how that engagement affected their learning, particularly in the context of the stressful online environment of the 2020 COVID-19 semester. Mixed-method data was collected from the assignments, which involved students: (i) solving an allocated problem and (ii) reflectively comparing their effort to an expert solution. Initially, many students did not engage with the scaffold due to viewing it as an “extra” work that needs to be done in addition to solving a problem. Through repeated assignment cycles, students showed greater engagement with the scaffold. Problem-solving success rate increased throughout the semester. By applying the scaffold to a range of chemical problems, students came to appreciate that it supported them in solving problems. Understanding students’ problem-solving processes will inform innovations in teaching problem solving
- …
