This study investigates exploratory search behaviors and learning outcomes from a metacognitive perspective, aiming to reveal the role of different metacognitive dimensions within the “search as learning” framework. A user experiment was conducted with 36 participants completing three types of exploratory search tasks. Data were collected through scales, screen recording analysis, and concept mapping, and analyzed using Spearman’s rank correlation analysis and multiple regression analysis. The results indicate that the influence of metacognitive abilities on exploratory search behaviors and learning outcomes varies significantly across task types: Decision-Evaluation tasks rely more on monitoring and evaluation, Planning-Oriented tasks highlight planning and regulation, while Knowledge-Acquisition tasks emphasize monitoring and evaluation in the processes of information accumulation and integration. Further regression analyses show that the explanatory power of metacognitive dimensions on learning outcomes differs by task type. These findings enrich the understanding of metacognition within the context of exploratory search as learning and provide practical implications for the design of more effective exploratory search systems.
AhnJWBrusilovskyP (2013) Adaptive visualization for exploratory information retrieval. Information Processing & Management49(5): 1139–1164.
2.
AthukoralaKGłowackaDJacucciG, et al. (2016) Is exploratory search different? A comparison of information search behavior for exploratory and lookup tasks. Journal of the Association for Information Science and Technology67(11): 2635–2651.
3.
BuYDingYXuJ, et al. (2018) Understanding success through the diversity of collaborators and the milestone of career. Journal of the Association for Information Science and Technology69(1): 87–97.
4.
CâmaraARoyNMaxwellD, et al. (2021) Searching to learn with instructional scaffolding. In: Proceedings of the 2021 conference on human information interaction and retrieval,pp.209–218.
5.
CarevicZLuskyMvan HoekW, et al. (2018) Investigating exploratory search activities based on the stratagem level in digital libraries. International Journal on Digital Libraries19: 231–251.
6.
ChenYQiuYLinH, et al. (2022) The effects of topic familiarity on college students’ learning search process. Aslib Journal of Information Management74(6): 1151–1173.
7.
ChenYZhaoYWangZ (2020) Understanding online health information consumers' search as a learning process: Search platform sequences, query reformulation and conceptual changes. Library Hi Tech38(4): 859–881.
8.
CoiroJ (2011) Predicting reading comprehension on the Internet: Contributions of offline reading skills, online reading skills, and prior knowledge. Journal of Literacy Research43(4): 352–392.
9.
CrescenziACapraRChoiB, et al. (2021) Adaptation in information search and decision-making under time constraints. In: Proceedings of the 2021 conference on human information interaction and retrieval, pp.95–105.
10.
CrescenziALiYZhangY, et al. (2019) Towards better support for exploratory search through an investigation of notes-to-self and notes-to-share. In: Proceedings of the 42nd international ACM SIGIR conference on research and development in information retrieval, pp.1093–1096.
11.
DiasMTV (2019) Understanding web search patterns through exploratory search as a knowledge-intensive process. Doctoral dissertation.
12.
EgusaYSaitoHTakakuM, et al. (2010) Using a concept map to evaluate exploratory search. In: Proceedings of the third symposium on Information interaction in context, pp.175–184.
13.
FlavellJH (1976) Metacognitive aspects of problem solving. In: ResnickLB (ed.) The Nature of Intelligence. Lawrence Erlbaum, pp.231–235.
14.
GagnièreLJalletALoretteM (2012) When metacognitive prompts help information search in collaborative setting. Computers in Human Behavior29(5): 1922–1930.
15.
GhoshSRathMShahC (2018) Searching as learning: Exploring search behavior and learning outcomes in learning-related tasks. In: Proceedings of the 2018 conference on human information interaction & retrieval, pp.22–31.
16.
GuoMZhouZGotzD, et al. (2023) Grafs: Graphical faceted search system to support conceptual understanding in exploratory search. ACM Transactions on Interactive Intelligent Systems13(2): 1–36.
17.
JungJSonSLeeS, et al. (2021) Throughhand: 2D tactile interaction to simultaneously recognize and touch multiple objects. In: Proceedings of the 2021 CHI conference on human factors in computing systems, pp.1–13.
18.
KangZ (2005) The preliminary construction of the scale for college student’s metacognitive ability. MA Dissertation, Shanxi University.
19.
LangYXieKGongS, et al. (2022) The impact of emotional feedback and elaborated feedback of a pedagogical agent on multimedia learning. Frontiers in Psychology13: 810194.
20.
LeiPLSunCTLinSSJ, et al. (2015) Effect of metacognitive strategies and verbal-imagery cognitive style on biology-based video search and learning performance. Computers & Education87: 326–339.
21.
LewZFlanaginAJ (2025) The influence of feeling-of-knowing on metacognitive processes in the digital media environment. Journal of Media Psychology Theories Methods and Applications37: 158–169.
LiYCrescenziAWardAR, et al. (2023) Thinking inside the box: An evaluation of a novel search-assisting tool for supporting (meta)cognition during exploratory search. Journal of the Association for Information Science and Technology74(9): 1049–1066.
24.
MaCZhangB (2018) A new query recommendation method supporting exploratory search based on search goal shift graphs. IEEE Transactions on Knowledge and Data Engineering30(11): 2024–2036.
25.
MalmbergJHaatajaEJärveläS (2022) Exploring the connection between task difficulty, task perceptions, physiological arousal and learning outcomes in collaborative learning situations. Metacognition and Learning17(3): 793–811.
26.
MarchioniniG (2006) Exploratory Search: From Finding to Understanding. Communications of the ACM49(4): 41–46.
27.
NgoDNguyenADangB, et al. (2024) Facial expression recognition for examining emotional regulation in synchronous online collaborative learning. International Journal of Artificial Intelligence in Education34(3): 650–669.
28.
PieschlS (2021) Will using the Internet to answer knowledge questions increase users’ overestimation of their own ability or performance?Media Psychology24(1): 109–135.
29.
RiehSYCollins-ThompsonKHansenP, et al. (2016) Towards searching as a learning process: A review of current perspectives and future directions. Journal of Information Science42(1): 19–34.
30.
SaitoHEgusaYTeraiH, et al. (2011) Changes in users’ knowledge structures before and after web search on a topic: Analysis using the concept map. Proceedings of the American Society for Information Science and Technology48(1): 1–4.
31.
SchopfTMachnerNMatthesF (2023) A knowledge graph approach for exploratory search in research institutions. arXiv preprint, arXiv:2311.15688.
32.
SunHJiangCDingZ, et al. (2016) Topic-oriented exploratory search based on an indexing network. IEEE Transactions on Systems Man and Cybernetics46(2): 234–247.
33.
TomoEMackenzieTJordanC, et al. (2007) How task affects information search. In: Workshop Pre Proceedings in Initiative for the Evaluation of XML Retrieval (INEX), Springer, pp.337–341.
34.
TsaiMJTsaiCC (2003) Information searching strategies in web-based science learning: The role of Internet self-efficacy. Innovations in Education and Teaching International40(1): 43–50.
35.
UrgoKArguelloJ (2022) Understanding the ‘pathway’ towards a searcher’s learning objective. ACM Transactions on Information Systems40(4): 1–43.
36.
VakkariP (2010) Exploratory searching as conceptual exploration. In: Proceedings of HCIR, pp.24–27.
37.
VakkariP (2016) Searching as learning: A systematization based on literature. Journal of Information Science42(1): 7–18.
38.
ValmoresKKDAcederaAP (2024) Influence of information needs and information seeking behavior on graduate school students’ literacy skills. British Journal of Multidisciplinary and Advanced Studies5(2): 10–23.
39.
VuongTDasPKRuotsaloT (2025) Associating cognitive abilities with naturalistic search behavior. Journal of the Association for Information Science and Technology76(4): 665–685.
40.
WhiteRWDruckerSMMarchioniniG, et al. (2007) Exploratory search and HCI: designing and evaluating interfaces to support exploratory search interaction. In: CHI’07 extended abstracts on Human factors in computing systems, pp.2877–2880.
41.
WuDDongJLiuC (2019) Exploratory study of cross-device search tasks. Information Processing & Management56(6): 102073.
42.
WuPZhangR (2022) Exploring the effects of health information seeking on e-satisfaction in online health communities: An empirical investigation. BMC Medical Informatics and Decision Making22(1): 332.
43.
XingYLiuP (2021) Research on users’ cognitive structure changes before and after exploratory search. Library and Information Service65(22): 74–84.
44.
YinJZhuYGohTT, et al. (2024) Using educational chatbots with metacognitive feedback to improve science learning. Applied Sciences14(20): 9345.
45.
YuanHZhangY (2020) Gamification design in exploratory search system. Journal of Modern Information40(4): 31–41.
46.
YuRGadirajuUHoltzP, et al. (2018) Predicting user knowledge gain in informational search sessions. In: The 41st international ACM SIGIR conference on research & development in information retrieval, pp.75–84.
47.
ZhouXWangXLiuX (2022) The impact of task complexity and translating self-efficacy belief on students’ translation performance: Evidence from process and product data. Frontiers in Psychology13: 911850.
Supplementary Material
Please find the following supplemental material available below.
For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.
For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.
