PARTIE 2 TRAVAUX EMPIRIQUES
5.6 Analyse des données collectées
Les données sur l’activité online étaient enregistrées grâce à l’outil libre de droit du navigateur Google Chrome : Chrome History View. Cet outil propose des fichiers logs détaillant l’activité de l’utilisateur (i.e. mots clés entrés au clavier, pages web vues, temps passé par pages etc). Les données étaient ensuite traitées via excel puis SPSS (version 21). Lorsque le protocole expérimental impliquait un traitement plus qualitatif (comme par exemple pour le traitement de l’activité des tâches mesurant les habiletés de recherche d’informations), la grille de codage était validée par plusieurs juges et un codage en double aveugle était réalisé sur quelques participants aléatoires pour en vérifier la robustesse.
Les prochains chapitres présentent sous format article les résultats des 4 expérimentations conduites pour ce travail de thèse (voir tableau récapitulatif 4 page 99) (articles publiés et intégrés dans ce document pour les chapitres 6 et 7 et articles soumis pour les chapitres 8 à 10).
Les chapitres 6, 7 et 8 (articles 1, 2 et 3) investiguent les effets de l’âge et des ressources apportées par les connaissances sur l’activité de RI selon le niveau de complexité des tâches. Les chapitres 9 et 10 (articles 4 et 5) traitent des deux outils d’aide à la RI élaborés (pré- activation des connaissances antérieures et aide au maintien du but de recherche en MDT).
Nous invitons les lecteurs à consulter les articles en démarrant par la partie méthode (pour éviter les redondances entre les parties introductions et la partie théorique de la thèse).
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Chapitre 6
Article 1: Sanchiz, M., Chin, J., Chevalier, A., Fu, W. T., Amadieu, F., & He, J. (2017). Searching for information on the web: Impact of cognitive aging, prior domain knowledge and complexity of the search problems. Information Processing and Management, 53(1), 281-294.125
Chapitre 7
Article 2: Sanchiz, M., Chevalier, A., & Amadieu, F. (2017). How do older and young adults start searching for information? Impact of Age, Domain Knowledge and Problem Complexity steps of Information Searching. Computers in Human Behavior, 72, 67–78. doi: 10.1016/j.chb.2017.02.038138
Chapitre 8
Article 3: Sanchiz, M., Amadieu, F. & Chevalier, A. Searching for information for well-defined and ill-defined search tasks with google search engine: predictors of young and older adults search strategies. (under review, 2017), Interacting with Computers.Les résultats présentés dans ce chapitre proviennent des données recueillies lors de l’expérience 2. Cet article, soumis à la revue Interacting with Computers, présente les données sur l’impact de l’âge, des connaissances antérieures, de la flexibilité et des habiletés de recherche d’informations dans le domaine films fantastiques pour les problèmes de RI bien définis (problèmes simples) et mal définis (problèmes multicritères) de l’expérience 1. Le lecteur trouvera en annexes les consignes des trois tâches évaluant les habiletés de RI ainsi que la grille de codage utilisée pour chacune (annexes 9a, b et c, p. 278-279).
Abstract
This study focuses on the interaction between age, information search skills, flexibility and domain knowledge. A specific task was designed to assess in-depth information search skills (operational interaction, navigational and text processing skills) with real on-line data that were then confronted to the search behavior of young and older users in well-defined and ill-defined search tasks. Results showed that older adults had poorer information search skills than young ones. Information search skills, flexibility and prior knowledge were better predictors than age alone of the search strategies used at the beginning of the search (when users elaborate their first query and process their first search engine result page), whereas age alone was a better predictor of the mean time spent on all search engine result pages. Navigational skills supported the exploration of new search paths whereas text processing skills supported in-depth exploration of the webpages opened up by older adults.
Keywords Psychology User studies Web search engine Age
User characteristics Activity centered design
139 1. Introduction
Though information search with search engines such as Google has become a widely common activity, it still induces some difficulties, particularly for older adults. Indeed, interacting with a search engine to search for information is challenging for older users as they have to elaborate non-linear search paths and navigate between several hyperlinks, process a large amount of information and produce queries. Prior works have shown that older users have difficulties interacting with search engines (Aula, 2005), they spend longer time analyzing the search engine pages (Hanson, 2010; Dommes, Chevalier, & Lia, 2011; Sanchiz, Chin, Chevalier, Fu, Amadieu, & He, 2017; Sanchiz, Chevalier, & Amadieu, 2017), they are less accurate (Pak & Price, 2008; Dommes et al., 2011) and they tend to have more difficulties selecting a website to open up than young ones (Chin & Fu, 2010). In addition, prior works demonstrated that older users particularly struggle for fact-finding tasks (as opposed to open-ended task that rely more on comprehension processes and sense-making). Searching for information with a search engine requires users to produce a query (i.e. a set of keywords) based on their search goal, process the results retrieved by the search engine pages (SERPs) and select a website to open up or reformulate their query. These actions involve several cognitive processes related to fluid abilities such as cognitive flexibility or processing speed (Cattell, 1971; Sharit, Hernandez, Czaja, & Pirolli, 2008). Cognitive flexibility, which refers to the ability to adapt to environment changes and switch to different processing strategies (Chevalier & Chevalier, 2009), is reported to be highly responsible for older adults’ difficulties to reformulate queries (Dommes et al., 2011). Prior works have shown that prior domain knowledge about the search topic can improve search performance (Pak & Price, 2008) and can cope with older adults’ difficulties by enhancing better search strategies (Sanchiz et al., 2017). However, prior studies carried out by Höslcher and Strube (2000) also showed that the benefits of prior domain knowledge only appeared when users had a certain level of skills related to the search task itself (Information search skills). Indeed, in their study, only domain experts and information search experts managed to directly select relevant webpages that contained the target information. Despite these findings, the role of IS skills in age-related differences is up to exploration. Some studies have attempted to analyze how IS skills could determine users’ search behavior with actual behavioral data and have shown that such measures are more reliable than self-assessing measures or questionnaires (Hargittai, 2002; Merritt, Smith, & Renzo, 2015; Van Deursen & Van Dijk, 2010; van Deursen et al., 2012). However most studies still assess IS skills with self- reported measures, web experience (such as years of internet use: Thatcher, 2008), internet
140 confidence (Crabb & Hanson, 2014) or educational level (Brand-Gruwel, Wopereis, & Vermetten, 2004; Hargittai & Hinnant, 2008). Though these methods can provide relevant measures, they also have some disadvantages: self-assessments can lead to overrating or underrating, especially for older ones (e.g. Marquié, Jourdan-Boddaert, & Huet, 2002) and the relation between internet use and concrete IS skills is not clear (van Deursen & van Dijk, 2010). In addition, prior works investigated the impact of IS skills and cognitive abilities on the whole search process and did not analyze their impact during the different stages of the search. The present study aimed at designing a task assessing in-depth IS skill on the basis of real on-line data and at testing whether cognitive flexibility, prior knowledge and IS skills could be better predictors of young and older adults’ search strategies with a search engine than age alone.