نوع مقاله : مقاله پژوهشی
نویسندگان
1 بخش علم اطلاعات و دانش شناسی. دانشکده علوم تربیتی و روانشناسی. دانشگاه شیراز
2 عضو هیات علمی گروه علم اطلاعات و دانش شناسی دانشگاه شیراز
3 گروه علم اطلاعات و دانش شناسی، دانشگاه شیراز
4 گروه علم اطلاعات و دانش شناسی، دانشگاه شیراز، شیراز، ایران.
چکیده
کلیدواژه‌ها
موضوعات
عنوان مقاله [English]
نویسندگان [English]
Purpose: This study tried to examine the role of task complexity in stopping information search behavior, including session-level stopping and query-level stopping among graduate students of Shiraz University.
Method: The current research is fundamental in terms of purpose, and quantitative considering data collection procedures. The statistical population consisted of graduate students of Shiraz University. Among them, 77 students were selected through judgmental sampling method. They were involved in searching for information in the thesis drafting stage and were willing to cooperate in the research, too. To conduct the study, eight tasks were designed using Repository of Assigned Search Tasks. After confirming the face validity of the tasks by Information Science professors, four experts in the field of task design determined the level of complexity of the work tasks in the form of a Likert scale. Finally, based on the experts’ viewpoints, two simple tasks and two complex tasks were selected. Students searched the tasks in the Google search engine while their transactions were recorded by Camtasia software (version 2019.0). Then, by observing users’ transactions with the search engine, the students’ stopping information search in each task was categorized into two groups of good stopping (i.e., stopping due to finding the answer to the question) and bad stopping (i.e., stopping due to not finding the answer to the question). The occurrence or non-occurrence of query-level stopping (query reformulation) was also recorded in each task. Noting that in order to provide the possibility of measuring the type of information search stop, good stop was coded with number 2 and bad stop with number 1.
After checking the normality of the data distribution using the Kolmogorov–Smirnov test, the significance of the effect of work task complexity on the type of stopping information search and the occurrence of query-level stopping were examined using Mann-Whitney U test and independent samples t-test using SPSS software, respectively.
Findings: The results indicated the effect of work task complexity on stopping information search; increasing task complexity led to a significant decrease in the rate of good stopping and an increase in the occurrence of query-level stopping. In other words, when doing complex tasks, the users reached the correct answer in fewer cases, and the search for these types of tasks was usually stopped due to the failure to find the answer. However, compared to simple tasks, users formulated more queries to complete these types of tasks and tried to find the (better) answer by repeatedly refining the query.
Conclusion: Understanding the effect of task complexity on stopping information search behavior can help human-information interaction researchers and designers of information retrieval systems in designing more user-oriented models for information search. It also helps users in more accurate query formulation and effective information retrieval.
کلیدواژه‌ها [English]
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