[Purpose/significance] This study uses learning-related search as the background to explore interactive behavior indicators that have a stable and significant impact on users' perception of the task difficulty. [Method/process] This research relied on course teaching to carry out behavior experiments. It took Information Technology Application course students as the research objects, used Morae to record search behavior experiments remotely. A total of 170 valid search behavior records from 39 students have been collected. According to the screen recording data and the task difficulty perception evaluation data, this study analyzed the behavior indicators which show significant differences under different difficulty levels. In addition, this study also combined two experimental data that carried out by the research team in 2016 and 2017 and the findings of existing related research, horizontal comparison was made, so as to summarize the stability of significant differences of behavior indicators under different task difficulty levels. [Result/conclusion] Finally, a stable behavior indicator system with 26 behavior indicators is obtained. The research also describes users' behavior characteristics in difficult tasks from the perspective of exploratory search process and behavior types, and points out the future research directions.
Huang Kun
,
Chen Jiaqi
,
Liu Chang
. Research on the Search Behaviors Oriented to Task Difficulty Perception[J]. Library and Information Service, 2022
, 66(3)
: 83
-92
.
DOI: 10.13266/j.issn.0252-3116.2022.03.010
[1] LIU J Q. Deconstructing search tasks in interactive information retrieval:a systematic review of task dimensions and predictors[EB/OL].[2021-10-29].https://doi.org/10.1016/j.ipm.2021.102522.
[2] LI Y L, BELKIN N J. A facted approach to conceptualizing tasks in information seeking[J]. Information process and management, 2008,44(6):1822-1837.
[3] KIM S, SOERGEL D. Selecting and measuring task characteristics as independent variables[EB/OL].[2021-10-29].https://doi.org/10.1002/meet.14504201111.
[4] CRESCENZI A, CAPRA R, ARGUELLO J. Time pressure, user satisfaction and task difficulty[J]. Proceedings of the American Society for Information Science and Technology, 2014, 50(1):1-4.
[5] 刘畅,宋筱璇,杨子傲.用户信息搜索中的学习行为及过程探究[J].大学图书馆学报,2019,37(4):36-45.
[6] 竺培梁. 心理测量——理论与应用[M]. 合肥:中国科学技术大学出版社, 2008.
[7] LIU J J, LI Y, HASTINGS S K. Simplified scheme of search task difficulty reasons[J]. Journal of the Association for Information Science and Technology, 2019,70(5):526-529.
[8] BELL D J, RUTHVEN I. Searcher's assessments of task complexity for Web searching[C]//Proceedings of the 26th European conference on information retrieval (ECIR 2004). Berlin:Springer, 2004:57-71.
[9] ARGUELLO J. Predicting search task difficulty[C]//Proceedings of European conference on information retrieval. Cham:Springer, 2014:88-99.
[10] LIU J J, GWIZDKA J, LIU C, et al. Predicting task difficulty for different task types[J]. Proceedings of the American Society for Information Science and Technology, 2010, 47(1):1-10.
[11] LIU J J, LIU C, COLE M, et al. Exploring and predicting search task difficulty[C]//Proceedings of the 21st ACM international conference on information and knowledge management. Maui:ACM, 2012:1313-1322.
[12] LIU C, LIU J J, BELKIN N J. Predicting search task difficulty at different search stages[C]//Proceedings of the 23rd ACM international conference on conference on information and knowledge management. Shanghai:ACM, 2014:569-578.
[13] 黄崑, 陈佳琦, 郑明煊, 等. 信息搜索任务难度研究述评[J]. 信息资源管理学报, 2020, 10(4):88-98.
[14] WILDEMUTH B M, KELLY D, BOETTCHER E, et al. Examining the impact of domain and cognitive complexity on query formulation and reformulation[J]. Information processing & management, 2018, 54(3):433-450.
[15] GWIZDKA J, SPENCE I. What can searching behavior tell us about the difficulty of information tasks? a study of Web navigation[J]. Proceedings of the American Society for Information Science and Technology, 2006, 43(1):1-22.
[16] KIM J. Task difficulty as a predictor and indicator of Web searching interaction[C]//Proceedings of CHI'06 extended abstracts on human factors in computing systems. Montréal:ACM, 2006:959-964.
[17] FIDEL R. Moves in online searching[J]. Online review. 1985, 9(1):61-74.
[18] ANDERSON L W, KRATHWOHL D R, AIRASIAN P W, et al. Taxonomy for learning, teaching, and assessing:a revision of Bloom's taxonomy of educational objectives[J]. European legacy, 2001, 114(458):1013-1014.
[19] KELLY D, ARGUELLO J, EDWARDS A, et al. Development and evaluation of search tasks for IIR experiments using a cognitive complexity framework[C]//Proceedings of the 2015 international conference on the theory of information retrieval. Northampton:ACM, 2015:101-110.
[20] BARZI F, WOODWARD M. Imputations of missing values in practice:results from imputations of serum cholesterol in 28 cohort studies[J]. American journal of epidemiology. 2004,160(1):34-45.
[21] 庞新生.缺失数据处理方法的比较[J].统计与决策,2010(24):152-155.
[22] DEMPSTER A P, LAIRD N M, RUBIN D B. Maximum likelihood from incomplete data via the EM algorithm[J]. Journal of the Royal Statistical Society, series B(Methodological), 1977, 39(1):1-38.
[23] 张路路,黄崑.基于认知风格的数字图书馆用户信息检索行为研究[J]. 情报学报,2018,37(11):1164-1174.
[24] BYSTRÖM K, JÄRVELIN K. Task complexity affects information seeking and use[J]. Information processing & management, 1995, 31(2):191-213.
[25] 王凯飞,黄崑.数字图书馆用户检索失败的影响因素研究[J].图书情报工作,2019,63(11):25-34.
[26] WHITE R W, ROTH R A. Exploratory search:beyond the query-response paradigm[J]. Synthesis lectures on information concepts, retrieval, and services, 2009, 1(1):1-98.
[27] AULA A, KHAN R M, GUAN Z. How does search behavior change as search becomes more difficult?[C]//Proceedings of the SIGCHI conference on human factors in computing systems. Atlanta:ACM, 2010:35-44.
[28] INTHIRAN A, ALHASHMI S M, AHMED P K. A user study on the information search behaviour of medical students[J]. Malaysian journal of library & information science,2015,20(1):61-77.
[29] DAN O, DAVISON B D. Measuring and predicting search engine users' satisfaction[J]. ACM computing surveys, 2016, 49(1):1-35.
[30] FRASER L, LOCATIS C. Effects of link annotations on search performance in layered and unlayered hierarchically organized information spaces[J]. Journal of the American Society for Information Science and Technology, 2001, 52(14):1255-1261.
[31] HU X, KANDO N. Task complexity and difficulty in music information retrieval[J]. Journal of the Association for Information Science and Technology, 2017, 68(7):1711-1723.
[32] HIENERT D, MITSUI M, MAYR P, et al. The role of the task topic in Web search of different task types[C]//Proceedings of 3rd ACM SIGIR conference on human information interaction and retrieval (CHIIR). New Brunswick:ACM, 2018:72-81.
[33] KUHLTHAU C C. Seeking meaning:a process approach to library and information services[M]. New York:Libraries Unltd Inc, 2004.
[34] DERVIN B. Sense-making theory and practice:an overview of user interests in knowledge seeking and use[J]. Journal of knowledge management, 1998, 2(2):36-46.
[35] NIU X, KELLY D. The use of query suggestions during information search[J]. Information processing & management, 2014, 50(1):218-234.
