Abstract
This study focus on queries formulation strategies when expert users in a medical or computer science domain solved complex tasks. Ten medical students and ten computer science students had to perform four fact-finding search tasks (two simple tasks and two inferential tasks) and six learning tasks (two exploratory, two decision-making and two problem solving tasks) in these two domains. Results showed that non-experts used more terms from task statement to build their queries than experts did. Experts often produced new keywords than non-experts did. Specifically, computer science experts used more keywords not specific to the domain knowledge whereas medical experts used specific domain keywords to formulate queries. These results are a beginning to better understand how users are searching to learn when they are using Internet but further ergonomics studies have to more explore this subject to create search systems adapted to Search as Learning activity.
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References
Campbell, D.J.: Task complexity: a review and analysis. Acad. Manag. Rev. 13(1), 40–52 (1988). https://doi.org/10.5465/amr.1988.4306775
Gwizdka, J., Hansen, P., Hauff, C., He, J., Kando, N.: Search as learning (SAL) workshop 2016. In: Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, pp. 1249–1250 (2016). https://doi.org/10.1145/2911451.2917766
Hembrooke, H.A., Granka, L.A., Gay, G.K., Liddy, E.D.: The effects of expertise and feedback on search term selection and subsequent learning. J. Am. Soc. Inf. Sci. Technol. 56(8), 861–871 (2005). https://doi.org/10.1002/asi.20180
Marchionini, G.: Exploratory search: from finding to understanding. Commun. ACM 49(4), 41–46 (2006). https://doi.org/10.1145/1121949.1121979
Monchaux, S., Amadieu, F., Chevalier, A., Mariné, C.: Query strategies during information searching: effects of prior domain knowledge and complexity of the information problems to be solved. Inf. Process. Manag. 51(5), 557–569 (2015). https://doi.org/10.1016/j.ipm.2015.05.004
O’Brien, H.L., Kampen, A., Cole, A.W., Brennan, K.: The role of domain knowledge in search as learning. In: Proceedings of the 2020 Conference on Human Information Interaction and Retrieval, pp. 313–317, Mars 2020. https://doi.org/10.1145/3343413.3377989
Rodon, C., Meyer, T.: Self-efficacy about information retrieval on the web across all domains: a short measure in French and English. Behav. Inf. Technol. 37(5), 430–444 (2018). https://doi.org/10.1080/0144929x.2018.1449252
Sanchiz, M., Amadieu, F., Chevalier, A.: An evolving perspective to capture individual differences related to fluid and crystallized abilities in information searching with a search engine. In: Fu, W.T., van Oostendorp, H. (eds.) Understanding and Improving Information Search, Human–Computer Interaction Series, pp. 71–96. Springer, Cham (2020). https://doi.org/10.1007/978-3-030-38825-6_5
Sanchiz, M., Chin, J., Chevalier, A., Fu, W.T., Amadieu, F., He, J.: Searching for information on the web: impact of cognitive aging, prior domain knowledge and complexity of the search problems. Inf. Process. Manag. 53(1), 281–294(2017a).https://doi.org/10.1016/j.ipm.2016.09.003
Sanchiz, M., Chevalier, A., Amadieu, F.: How do older and young adults start searching for information? Impact of age, domain knowledge and problem complexity on the different steps of information searching. Comput. Hum. Behav. 72, 67–78 (2017b).https://doi.org/10.1016/j.chb.2017.02.038
Sharit, J., Taha, J., Berkowsky, R.W., Profita, H., Czaja, S.J.: Online information search performance and search strategies in a health problem-solving scenario. J. Cogn. Eng. Decis. Making 9(3), 211–228 (2015). https://doi.org/10.1177/1555343415583747
Tamine, L., Chouquet, C.: On the impact of domain expertise on query formulation, relevance assessment and retrieval performance in clinical settings. Inf. Process. Manag. 53(2), 332–350 (2017). https://doi.org/10.1016/j.ipm.2016.11.004
Vakkari, P.: Searching as learning: a systematization based on literature. J. Inf. Sci. 42(1), 7–18 (2016). https://doi.org/10.1177/0165551515615833
Acknowledgments
The French National Research Agency (ANR), CoST-Modelling Complex Search Tasks (ANR-18-CE23-0016), supported this research.
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Dosso, C., Tamine, L., Paubel, PV., Chevalier, A. (2022). The Impact of Expertise on Query Formulation Strategies During Complex Learning Task Solving: A Study with Students in Medicine and Computer Science. In: Black, N.L., Neumann, W.P., Noy, I. (eds) Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021). IEA 2021. Lecture Notes in Networks and Systems, vol 223. Springer, Cham. https://doi.org/10.1007/978-3-030-74614-8_77
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