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004-rq.Rmd
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004-rq.Rmd
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# Research Questions {#ch-rq}
<!-- ## Research Questions {#sec-rq} -->
Combining empirical findings and gaps in the literature from the disciplines of Education (Chapter \@ref(ch-bg-learn)) and Information (Chapter \@ref(ch-bg-search)), we saw that:
- searching for information online is an integral part of new learning (Section \@ref(sec-bg-learn-info-eval))
- learning happens when students connect new pieces of information to their existing knowledge structures via assimilation, restructuring, or tuning (Section \@ref(sec-bg-learn-sensemaking)), and this process is influenced by the learner's individual traits (Section \@ref(sec-bg-learn-promoting-learning))
- modern knowledge-work requires less of long term memory, and more of creation of knowledge-artefacts, which should be treated as better assessors and outcomes of learning (Section \@ref(sec-bg-learn-artefact))
- domain expertise and search behaviour are strongly linked (Section \@ref(sec-bg-search-expertise))
- learning is a process that takes place longitudinally over time (Sections \@ref(sec-bg-learn-sensemaking) and \@ref(sec-bg-learn-principles)), yet only a handful of studies (mostly over a decade ago) have investigated the intertwined process of searchers' learning and their information searching behaviour over time (Section \@ref(sec-bg-search-longitudinal-studies))
- this creates acute gaps in our knowledge about long term information searching and learning behaviour, which is crucial for building learning-centric search systems of the future, which can support sensemaking and knowledge-gain
Guided by the above insights, we ask the following research questions in this dissertation, and aim to answer them via an exploratory longitudinal study of students' information search behaviour and learning outcomes over the course of a university semester (Section \@ref(sec-method-exp-design)).
> **RQ1:** *How do (changing) individual differences of students affect their longitudinal information search behaviour?*
\
\
> **RQ2:** *What are the similarities and differences in information search behaviours for tasks where the learning goals are new (non-repeated search tasks), versus those where the learning goals are repeated (repeated search tasks)?*
\
\
> **RQ3:** *How do (longitudinal) information search behaviour of students relate to their (self-perceived) learning outcomes?*
The study was purposefully planned to be exploratory in nature [@stebbins2001exploratory].
Therefore, the research questions are exploratory as well, meant at discovering interesting patterns, and aiming to illuminate new concepts through quantitative observation.
Students' motivation, self-regulation and metacognition capabilities determine, direct, and sustain the approaches they take to learn (Section \@ref(sec-bg-learn-promoting-learning)).
Effective searching for learning is affected by students' search tactics and information evaluation capabilities (Section \@ref(sec-bg-learn-info-eval)) as well as cognitive capabilities, such as memory span (Section \@ref(sec-bg-search-expertise)).
We (weakly) hypothesize that students showing sustained or increasing values of metacognition, self-regulation, and motivation over the duration of the semester will put more effort into their searches, and demonstrate better learning and search outcomes.
Learning and expertise are closely connected: expertise is an evolving characteristic of learners that reflects learning over time, rather than being a static property [@rieh2016searching].
Domain expertise and search behaviour has been studied, albeit mostly during single lab sessions, and sometimes longitudinally (Section \@ref(sec-bg-search-expertise)).
Therefore, there is a clear gap in understanding how higher education students search for information in the long term, how their information use behaviour develop over time, and how it affects their learning [@zlatkin2021students].
The three research questions presented in this chapter aim to address some of these gaps.
<!--
For the purposes of this dissertation, we considered learning as change in a student's knowledge about certain topics over the duration of a university semester.
The research questions are first stated in this section, to put them all
together in one place for easy reference. Then the overarching
hypotheses are discussed in Section \@ref(sec-rq-hypotheses).
> **RQ1:** *What kind of longitudinal information search behaviours are correlated to the degree of change in students' knowledge levels and learning outcomes?*
\
\
> **RQ2:** *What are the similarities and differences in information search behaviours for tasks where the learning goals are new (new search tasks), versus those where the learning goals are repeated (repeated search tasks)?*
\
\
> **RQ3:** *How does externalisation and articulation affect students' learning outcomes and experiences during search?*
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> **RQ4:** *How do (changing) individual differences of students moderate their information search behaviours and learning outcomes?*
## Overarching Hypotheses {#sec-rq-hypotheses}
In this Section, we discuss the research framework and hypotheses behind
the research questions. The study is primarily planned to be
exploratory, therefore the hypotheses are exploratory in nature as well.
### Learning as Students' Transition from Novice to Expert (RQ1, RQ2) {#sec-framework-rq1-rq2}
Learning and expertise are closely connected: expertise is an evolving
characteristic of learners that reflects learning over time, rather than
being a static property [@rieh2016searching]. Domain expertise and
search behaviour has been studied, albeit mostly during single lab
sessions, and sometimes longitudinally (Section \@ref(sec-bg-search-expertise)). There is a clear gap in
understanding how higher education students search for information in
the long term, how their information use behaviour develop over time,
and how it affects their learning [@zlatkin2021students]. RQ1 and RQ2
aims to address some of these gaps.
**Hypothesis for RQ1:** Search behaviours described in Table \@ref(fig:search-behaviours) will occur both within individual search sessions, and across progressive search sessions recorded over a semester, as domain expertise of students increases [@eickhoff2014lessons].
**Hypotheses for RQ2:** This research question stems from the idea of lifelong or continuous learning: how do search behaviours evolve over time when gaining knowledge about perpetual life skills (e.g., financial literacy). We hypothesize that
- relevance judgement of previously viewed information on this topic will change over time, as searcher gains more knowledge and expertise
- the decision or choice to put effort into searching again, or satisfice with previously found information, will have links to motivation and self-regulation
### Promoting Better Learning (RQ3, RQ4) {#sec-framework-rq3-rq4}
Better learning takes place when students articulate and their unformed
and still developing understanding, and continue to articulate it
throughout the learning process (Section \@ref(sec-bg-learn-articulation)). Also, students' motivation,
self-regulation and metacognition capabilities determine, direct, and
sustain the approaches they take to learn (Section \@ref(sec-bg-learn-promoting-learning)). Effective searching for
learning is affected by students' search tactics and information
evaluation capabilities (Section \@ref(sec-bg-learn-info-eval)) as well as cognitive capabilities
such as memory span (Section \@ref(sec-bg-search-expertise)).
**Hypothesis for RQ3:** articulation during the search as learning
process (via concurrent think aloud) will lead to better learning (and
possibly better searching) outcomes, than working silently.
**Hypotheses for RQ4:** with respect to the individual differences and
contexts in which students search to learn, we speculate the following
hypotheses:
- students showing sustained or increasing metacognition,
self-regulation, and motivation over the duration of the semester
will put more "effort" into their searches, and demonstrate better
learning and search outcomes
- students with higher memory span will demonstrate more 'branchiness'
and parallel browsing in their search behaviour
- students with better information evaluation capabilities will
demonstrate better learning and search outcomes
-->
<!--
## Anticipated Contributions {#sec-rq-diss-contributions}
We anticipate by answering the proposed research hypotheses and
question, the results can greatly contribute to the existing knowledge
of Interactive Information Retrieval and Educational Sciences in
general, and Search as Learning in particular. Referring back to some of
the research agenda advocated by the multiple workshops and journal
special issues on Search as Learning (Section
\@ref(sec-intro-outline)), our research questions aim to
investigate *(i)* the contexts in which students search to learn; *(ii)*
the factors that influence their learning outcomes; and *(iii)* whether
students are more critical consumers of information.
Many researchers have expressed their concern with the lack of
longitudinal studies in IIR and related domains
[@zlatkin2021students; @kelly2009evaluation; @koeman2020hciux]. If
significant relationships were to be found between students' information
search behaviours and learning outcomes, the results of this
dissertation can provide great insights and contributions towards *(i)*
understanding how search behaviours can predict learning outcomes;
*(ii)* creating reliable measures, methods, and instruments for
capturing changes in people's knowledge level, learning experiences, and
learning outcomes [@url-rieh-homepage]; and *(iii)* developing search
systems that better support learning and sensemaking.
-->