=Paper=
{{Paper
|id=Vol-2699/paper19
|storemode=property
|title=Working Towards the Ideal Search History Interface
|pdfUrl=https://ceur-ws.org/Vol-2699/paper19.pdf
|volume=Vol-2699
|authors=Tetiana Tolmachova,Eleni Ilkou,Luyan Xu
|dblpUrl=https://dblp.org/rec/conf/cikm/TolmachovaIX20
}}
==Working Towards the Ideal Search History Interface==
https://ceur-ws.org/Vol-2699/paper19.pdf
Working Towards the Ideal Search History Interface
Tetiana Tolmachovaa , Eleni Ilkoua and Luyan Xub
a L3S Research Center, Leibniz Universität Hannover, Hannover, Germany
b DEKE Lab (MOE), Renmin University of China, Beijing, China
Abstract
Searching on the Web has become an essential part of learning, and bookmarking is a way to remember relevant and inter-
esting sites. Even though bookmarking systems have been around since the dawn of the Web, they have not evolved much
in the last 20 years. In this paper, we introduce LogCanvas v2, a new and extended design of the search history interface,
intended to capture the search and learning process in our Learnweb educational platform. Our new interface focuses on
users’ queries rather than just the browsed webpages, enabling users to reconstruct the searching, browsing and learning
process. Also, it helps them to re-find the information they need and annotate the useful information. We hypothesize that
search learning with annotation capabilities can be achieved in our platform. We finish the paper with a detailed description
of a learning scenario and the benefits of the learning process in our platform.
Keywords
Search history visualization, information re-finding, collaborative search
1. Introduction the user experience in searching to learn scenarios, when
users want to revisit certain webpages to review what
Searching to learn is increasingly viable as more ma- they have learned during the searching process? To an-
terials become digital and get published on the web. swer this question, we carried out a comparative study
Learning searches involve multiple iterations of queries of user experience in using history interfaces of popu-
and return sets of objects that require cognitive pro- lar search engines to review webpages while searching
cessing and interpretation. During this process, sear- to learn (see Section 3). Based on the results of this in-
chers’ interactions with search systems is generally vestigations, we propose a new design for the search
recorded as search history logs. Studies found that as engine history interface, the LogCanvas v2. In con-
many of 40% of users’ search queries are attempts to trast to the existing interfaces, the LogCanvas v2 fo-
re-find previously encountered results [1]. Further, a cuses more on the users’ searching and browsing path,
survey of experienced Web users showed that people such as how users issued queries and navigated to cer-
would like to use search engines to re-find online in- tain search results; which enables them to reconstruct
formation, but often have difficulty remembering the their searching, browsing and learning process to help
sequence of queries they had used when they origi- them re-find information quickly.
nally discovered the content in question [2]. In this This paper is organized as follows: in Section 2, we
scenario, search history can be an important resource provide an overview of related literature about exist-
for both individuals and collaborative searching groups ing search history visualization platforms. In Section 3,
to preserve and recall their searching and learning pro- we discuss users’ experience in using current search
cess. engines’ history interfaces and their feedback. In Sec-
Search logs record explicit activities of searchers, tion 4, we describe our design and the workflow of the
including the submitted queries and the clicked an- LogCanvas v2 history interface. An experimental sce-
swers (search results). The history interface in cur- nario in which we plan to evaluate Learnweb is pre-
rent search engines displays the issued queries with sented in Section 5. Finally, we draw our conclusions
corresponding visited webpages in the form of a URL in Section 6.
list. However, there is a research question that might
arise: is the current history interface well-designed for
2. Related Literature
Proceedings of the CIKM 2020 Workshops, October 19–20, Galway,
Ireland Research on searching as learning and archived data
email: tolmachova@l3s.de (T. Tolmachova); ilkou@l3s.de (E. visualization is relevant to our work, as it concerns
Ilkou); xuluyan@ruc.edu.cn (L. Xu) searching platforms that support learning during search-
orcid: 0000-0002-0751-6806 (T. Tolmachova); 0000-0002-4847-6177
(E. Ilkou)
ing, preserving and visualizing users’ search histories.
© 2020 Copyright for this paper by its authors. Use permitted under Creative
Commons License Attribution 4.0 International (CC BY 4.0).
CEUR
Workshop
Proceedings
http://ceur-ws.org
ISSN 1613-0073 CEUR Workshop Proceedings (CEUR-WS.org)
2.1. Searching as Learning work “Interfaces to support collaboration in informa-
tion retrieval” [11]. The key idea was to develop an in-
Some existing studies have focused on the correlation
terface, which allows to collect the user’s queries and
between learning and users’ searching progress. Re-
their results, and after that to visualize the search pro-
searchers such as Vakkari [3] and Wildemuth [4] have
cess.
explored the role of information searching in learn-
A more recent solution is SearchX [12], which is
ing, and the factors or concepts related to searching as
based on the search engine Pineapple Search1 . SearchX2
learning. Freund et al. [5] found that reading could be
is a search system, which includes a collaborative search
the core component of users’ searching progress, and
interface. People can collaborate in groups during the
they studied the text on the impact of learning out-
searching process by using different widgets, such as
comes.
shared query history with the groupmates, bookmarks
Extensive studies have also been conducted on sear-
of useful information and sites which can be seen and
ching systems or techniques in supporting learning.
used by other people in the group.
Stange et al. [6] investigated users’ searching progress
Systems such as popHistory [13] and Warcbase [14,
and found that individuals could integrate their knowl-
15] save users’ visit data, based on which they can ex-
edge gains into the searching process through concept
tract and display the most visited websites to users.
maps, and understand the relationship between learn-
History Viewer [16] tracks processes of exploratory
ing, sense making, and information seeking. Egusa et
search and presents users with interaction data to en-
al. [7] revealed that the visualization tools in search
able them to revisit the steps that led to particular in-
engines, such as concept maps, could be used to eval-
sights.
uate evolvement of users knowledge structure and
Information re-finding tools such as SearchBar [17]
search behaviours. Jansen et al. [8] classified searching
provide a hierarchical history of recent search topics,
as learning tasks of users to verify whether there were
queries, results and users’ notes to help users quickly
specific factors in the learning process. Moreover, they
re-find the information they have searched. The sys-
found that web searchers relied more on their knowl-
tem Personal Web Library helps users to understand
edge and information needs, while the searching was
their web browsing patterns, identify their topics of
used mainly to check facts.
interest and retrieve previously visited webpages more
There were also studies focusing on how the per-
easily [18]. Some other tools, such as SIS (Stuff I’ve
formance of searching as learning can be improved by
Seen) [19], collect users’ personal data, such as email
assistance of new models, systems, and other meth-
and docs, and offer a diary list to help users quickly lo-
ods. Saito et al. [9] designed a searching platform that
cate past events or visited web-pages based on dates.
supports users thinking activities. The platform visu-
Some recent works [20, 21] investigated how to com-
alized learners’ searching process and promote their
bine context analysis and information re-finding frame-
thinking by comparing learners’ searching as learn-
works to remind users about historical events accord-
ing processes to those of other searchers. Bah and
ing to users’ current context. Logcanvas [22] and Log-
Carterette [10] created a system to support continu-
CanvasTag [23] provided a graph-based search history
ous searching as learning. The system firstly created
visualization helping users re-construct the semantic
typical pseudo-documents and then sorted informa-
relationship among their search activities.
tion from retrieval results according to how closely it
In collaborative search systems such as Coagmen-
matched the typical document.
to [24] and SearchTogether [25], visualization of search
Existing studies have shown that learning is em-
history usually involves multiple users’ search logs,
bedded in the searching processes. However, these
including their search queries, and bookmarks. Inter-
works are focused more on developing dedicated sys-
faces of this kind display search histories separately
tems and single-user scenarios, and more studies are
according to data types or categories and support note-
needed that focus on searching as learning within
pad functions which allow group members to share an
search engines and more complex scenarios such as
experience.
collaborative web search.
By contrast to the systems described above, Log-
Canvas v2 provides a visualization of the search ses-
2.2. Archived Data Visualization sions based on a timeline and tags the activities of users.
One of the first works regarding developing an inter- Our aim is to help users to reconstruct easily their
face for collaborative learning was published in 1996
1 https://www.pineapplesearch.com/
by Michael B. Twidale and David M. Nichols in their 2 https://github.com/felipemoraes/searchx
Table 1
A comparison between functions of Pocket, Google, and Learnweb
Items Learnweb Pocket Google
i. Private Resources
(bookmarked or archived) i. Private Resources
Searching scope i. Private Resources
ii. Topical Groups (bookmarked or archived)
iii. Archived documents
Full-text search Keyword search or URL
Searching method Full-text search
(Bing API & Solr) (exact matching)
Bookmarking guideline Bookmarking guideline Bookmarking guideline
Bookmarking method
within platform in form of plugin within platform
i. Filter i. Filter
Operations on
ii. Rate (i.e. add type) ii. Rate (i.e. add favorite)
bookmarked/archived —
iii. Tag iii. Tag
resources
iv. Comment iv. Search by tag
i. Topical groups
Organizing bookmarked/
ii. Folders Tags Folders
archived resources by:
iii. Tags
Collaborative Annotation
Support for learning searching and with content on —
history sharing saved webpages
searching process and re-find an information which tem to support users independent or collabora-
they searched for. tive search, its history interface was designed to
support varied retrieving scopes including: pri-
vate resources, wherein a user’s individual sear-
3. An Investigation of Web ching records can be found; topical groups, whe-
History Interfaces rein queries and search results of members in
the user’s collaboration group can be found; ar-
In this section, we compare history-related functions chived documents, wherein the search results
in three searching platforms: Google Search, Pocket, archived by the user can be found. On the con-
and Learnweb3 . Learnweb is a web platform, devel- trary, Pocket and Google Search support retrieval
oped for searching, collecting and sharing educational within users’ individual searching records.
resources [26, 27]. In order to understand what might 2. Searching method. In the Learnweb platform
be missing in the current version of Learnweb, we in- and in Google Search users can do a full-text
vestigated which functionalities are offered to the users search to retrieve histories. Pocket only pro-
from their search histories. As shown in Table 1, we vides keyword search and search by URL (exact
compared the history-related functions of the three plat- matching).
forms from different perspectives: (i) history retriev-
Bookmarking By applying the “bookmark” function
ing (i.e. searching scope, searching method), (ii) book-
during searching, users can mark important search re-
marking (i.e. bookmarking method, operations on
sults for quickly information re-finding or reviewing
bookmarked resources, and bookmarking organizing
in the future. In the three analysed platforms, book-
method), and (iii) support for learning.
marking methods and supporting operations on book-
marked resources are different.
History retrieving Being able to review queries and
search results quickly is considered as a highly use- 1. Bookmarking method. In Learnweb and Google
ful feature of a history interface. In all the three re- Search, users can directly bookmark search re-
viewed interfaces, users can review their search histo- sults through a pop-up guideline within the plat-
ries (i.e. queries, search results and bookmarked re- form. When using Pocket to store webpages, a
sources). However, there are still differences as re- Pocket plugin should be added to the search en-
gards history retrieving scope and retrieving methods. gine.
2. Operation on bookmarked/archived resources.
1. Searching scope. Since Learnweb was developed Using the Learnweb platform and Pocket users
to be a collaborative searching and archiving sys- can edit metadata of archived resources includ-
3 https://learnweb.l3s.uni-hannover.de/ ing ratings, tags and comments. Besides this, in
Figure 1: LogCanvas v2 interface displaying the search history results.
Pocket users can select and highlight the text of and project-based learning [30], short term or long term,
a resource and review all the highlights. In the can be achieved. In order to achieve TBL, students
Chrome browser, users can only change the file should work in small groups, be accountable for the
name and the file location. work they are performing, and receive feedback [31].
3. Organizing bookmarked/archived resources. A In order to achieve the maximum impact in learning,
possibility of organizing saved resources is pre- the groups should work on different parts of the same
sent in all three interfaces. In Learnweb, a user problem, which demonstrates a useful concept and re-
can organize the resources by topical groups, port simultaneously. Focused on these goals we de-
folders and tags; in Pocket by tags and in Chrome veloped a learning scenario to test our platform (Sec-
by folders. tion 5.1).
Support for Learning The Learnweb platform can fa-
cilitate distance learning. By using web resources, stu- 4. The Design of LogCanvas v2.0
dents can learn asynchronously from any place with
an internet connection. According to our analysis, Having a better knowledge of existing solutions, we
Learnweb is outstanding in terms of supporting learn- started to design a new search history interface to be
ing during searching. It provides learning-related func- integrated into the Learnweb platform.
tions that allow users to work in topical groups, join
specific courses and perform data analysis of their work
4.1. Overview
or their groupmates [28]. On the other hand, we no-
ticed that Pocket, as a history manager, supports anno- The LogCanvas v2 search history interface is used to
tating for articles or videos in bookmarked webpages recover the search history from the Learnweb plat-
where users can directly add their comments or per- form. The interface was inspired by different web-
sonal ideas to the saved resources. This kind of in- browsers, such as Google Chrome, Firefox and Safari.
teraction between users and search history is shown The latest version of the interface focuses more on the
to be effective in supporting learning during the in- users’ queries and has several new features in compar-
formation searching/re-finding process [29]. Thus, we ison to the previous versions.
explored the possibility of adding a similar function to In order to record the searching process, first of all,
Learnweb (as described in Section 4). users have to perform some search queries in Learnweb.
Moreover, in Learnweb team-based learning (TBL) After registration and login into the platform, the user
Figure 2: An external webpage with an opened Hypothes.is client. By clicking in the first webpage “Shaman Energy Drink"
in Figure 1, we are redirected here.
is redirected to the main page and can perform a search 4.2. Collaborative Work with
using the navigation panel, which is also located on Annotation Features
each page of the platform, as it is visible in Figure 1 (A).
Each internal webpage also has a breadcrumb naviga- During a preliminary evaluation of our prototype, we
tion (e.g. “Search history”) as shown in Figure 1 (B). noticed that a connection between the search history
The resulting search history page is divided into two results and the original searching process was miss-
parts: a search sessions list with all logged queries, ing. In particular, while revisiting the search history
where in Figure 1 (C) the query “shaman...ingredients” results and the resources stored in the personal folders,
is selected to check the corresponding search history; it was difficult for the user to reconstruct the searching
and a list of the archived web results (i.e. snippets) as context and the links to the original webpages; for ex-
displayed in Figure 1 (D). To recover the search his- ample to remember why a specific resource had been
tory and snippets, a user has to choose a query from selected to be stored instead of others.
the sessions list panel. This panel includes three ele- For this reason, we decided to introduce webpage
ments: a button to switch between the personal search annotations in order to provide the missing informa-
history and the history generated by other members of tion. Among other annotation tools we choose Hy-
a common group, a search bar that allows quick filter pothes.is4 and integrated their client into Learnweb
through all users’ sessions and queries, and a timeline ecosystem. It allows taking notes directly on online
of all search sessions by descending order. webpages or in PDF-documents, and displays an over-
By clicking on one of the queries from the session view of all annotation activities, as it shown on Fig-
list, a list of snippets of archived search results will ure 2, where all the highlighted and annotated text
be opened on the right side of the window, wherein were taking on the webpage of “Shaman Energy Drink”.
all visited snippets are highlighted for a quick review. All annotated parts of the webpage are shown in the
The visited snippet “Shaman Energy Drink” is high- right panel (Fig. 2 (B)). By clicking on one of the anno-
lighted as an example in Figure 1 (D). A filter allows to tations, on the webpage will be highlighted the chosen
choose which snippets to visualize: only the snippets part of the text (Fig. 2 (A)), and vice versa. More specif-
that were visited during the searching process, or to ically, in Figure 2 (A) the annotated website where the
display all the snippets as they were shown in the orig- content “SHAMAN...long-lasting..” is highlighted; and
inal rank on the web results page. The clicked snippets in Figure 2 (B) the annotating panel containing all com-
are highlighted for easier recovering of the searching ments of team members is displayed, where in our ex-
process (marked with green and has the hand icon). 4 https://hypothes.is/
ample the user “tania_tol” added an annotation “Ingre- and the learning components of learning scenarios.
dients” to the previous highlighted content. Title: Which energy drinks are poor for health?
Target group: High school students (15-18 years old)
4.3. Learning Assumption in Chemistry class, working in teams of 2-3 people.
Estimated duration: 3 hours.
For the evaluation of the LogCanvas v2 search his- Learning environment: Online.
tory interface, we formulate the following learning as- Learning outcomes: To research and gather infor-
sumption, which we plan to evaluate with a specific mation from online search; to know about chemical
learning scenario. We argue that an annotation sys- components that commonly exist in energy drinks and
tem in combination with the search history can their effects on health; to learn which energy drinks
be a useful tool for users in group projects, and contain (larger) doses of unhealthy components; to en-
can improve the teaching and learning experience. hance learning through student collaboration and new
In previous studies [32, 33], we find remarks for ben- forms of assessments; to work and collaborate in a
efits of using annotations, such as highlighted text, team; to organize ideas and data, and present them in
comments, and tags, as a useful and easy way to achieve front of their peers; to organize and present a final re-
collective work in an online domain. Annotations on a port.
search base can reveal the insights of group activity in Learning scenario: Students are asked to form groups
collaborative work. Hence, they help teachers and stu- of 2 to 3 people in the chemistry class. The teacher
dents track the thought and learning process by iden- presents the project definition and explains the two
tifying the search results over time, and at the same parts of the project. In the first part, students should
time document the references which were used to find do research in order to identify the most common un-
the students’ answers. This is profitable for students healthy ingredients in the energy drinks. Second, they
because based on the search results of their classmates, will pick an ingredient - after discussing with the tea-
they decide to revisit a webpage or not. Documenting cher, so each team picks a different one - and search
the search process with annotations can help students, about the energy drinks which include this ingredient;
also in motivating their choices while preparing the or if all energy drinks contain it, then pick the ones
final course presentation. Further, it is effective for with higher concentration. The final results of each
teachers as they can view the students’ activity and team will be reported in a brief report and presented
trace their resources. Therefore, we hypothesize that in front of the class.
joint work projects can be achieved in the Learnweb Future perspectives: This scenario can be further ex-
platform successfully. tended as a multidisciplinary project with the sports
science class. Additionally, it could interest university
lectures related to health, diet and sports to perform
5. Experimental Scenario similar learning scenario as (part of) a project-based
evaluation.
In this section we present the learning scenario we de-
Evaluation: The students present their results in a re-
signed to test the learning assumption on the Learnweb
port and prepare a presentation.
search engine (Section 5.1), as well the user experience
while completing the learning scenario in Learnweb
(Section 5.2). 5.2. Execution of the Scenario in
Learnweb
5.1. Learning Scenario To perform the task, students have to search for web-
The Learnweb platform offers the ability to perform sites containing useful information about energy drinks.
a wide variety of learning scenarios, based on the re- In a preliminary experiment, students needed about
quirements and the needs of each course. Team-based, 10 queries and visited about 20 websites to find all re-
project-based, and distance learning scenarios, like the quired answers. A similar search process is displayed
one described here, can successfully be executed. in Figure 1. These answers can be highlighted/annota-
The design of this learning scenario was based on ted in the new Learnweb platform, and all highlighted
the essential elements for TBL. Its development is in- texts, annotations and websites are added to a spe-
fluenced by a template [34] and examples for collabo- cial annotations file in the students work-space. This
rative learning5 that analytically present the structure helps students document their work and offers them
the ability to prove their process to other team mem-
5 http://colab.eun.org/learning-scenarios bers; by the timestamp and users name on each anno-
tation. The latter promotes their individual account- sation of a longitudinal study, Journal of docu-
ability and aids the accountability of each member for mentation (2001).
contributing to the team based on the TBL [31]. Fur- [4] B. M. Wildemuth, The effects of domain knowl-
thermore, it creates a proof of work for the work car- edge on search tactic formulation, JASIST (2004).
ried by each member to the teacher. [5] L. Freund, R. Kopak, H. O’Brien, The effects of
Additionally, it helps other team members realise textual environment on reading comprehension:
the results of their teammates tag, share, highlight or Implications for searching as learning, Journal of
comment them, as it is displayed in Figure 2. In this Information Science (2016).
way, the team can collaborate and each team member [6] D. Stange, H. Heyn, A. Nürnberger, Capturing in-
can critically comment others observations and find- formation gain in information seeking with con-
ings. Further, it offers the ability for quick and pre- cept maps, in: Searching as Learning Workshop
cise feedback from the teachers, for the intermediate IIiX, 2014.
outcomes. [7] Y. Egusa, M. Takaku, H. Saito, How to evaluate
Finally, the annotations file is helpful for the final searching as learning, in: Proceedings of Search-
evaluation. It can help students identify quickly the ing as Learning Workshop (IIiX 2014 workshop),
important webpages and the specific parts of useful 2014.
information, which they have annotated during their [8] B. J. Jansen, D. Booth, B. Smith, Using the
work on the project. Moreover, it easily links to all taxonomy of cognitive learning to model online
used resources, letting no information untraceable. Fur- searching, Information Processing & Manage-
thermore, it displays each member contribution to the ment (2009).
team’s output; by checking the annotations file; and [9] H. Saito, K. Miwa, Construction of a learning en-
the collaboration’s between the team; by analysing the vironment supporting learners’ reflection: A case
comments, tags and highlights to other team members of information seeking on the web, Computers &
content. Education (2007).
[10] A. Bah, B. Carterette, Using ‘model’pseudo-
documents to improve searching-as-learning and
6. Conclusion search over sessions, in: Searching as Learning
Workshop IIiX, 2014.
In this paper, we introduce LogCanvas v2 - a new and
[11] M. Twidale, D. Nichols, Interfaces to support
extended design of the search history visualization in
collaboration in information retrieval, Informa-
our Learnweb educational platform. The new inter-
tion Retrieval and Human Computer Interaction
face documents the complete search and learning pro-
(1996).
cess of students in a distance learning, team-based and
[12] S. R. Putra, F. Moraes, C. Hauff, Searchx: Empow-
project-based learning scenario. All visited websites
ering collaborative search research, in: SIGIR ’18,
are documented, relevant sections of the websites
2018.
which provide answers to the student are highlighted,
[13] M. Carrasco, E. Koh, S. Malik, pophistory: An-
annotated and discussed by the students. This makes
imated visualization of personal web browsing
the writing of the final report much easier for the stu-
history, in: CHI ’17, 2017.
dents and makes sure all references are included in this
[14] J. Lin, Scaling down distributed infrastructure on
report.
wimpy machines for personal web archiving, in:
WWW ’15, 2015.
References [15] J. Lin, M. Gholami, J. Rao, Infrastructure for
supporting exploration and discovery in web
[1] J. Teevan, E. Adar, R. Jones, M. A. Potts, Informa- archives, in: WWW ’14, 2014.
tion re-retrieval: repeat queries in yahoo’s logs, [16] V. C. Segura, S. D. Barbosa, History viewer: dis-
in: SIGIR ’07, 2007. playing user interaction history in visual analyt-
[2] A. Aula, N. Jhaveri, M. Käki, Information ics applications, in: HCI ’16, 2016.
search and re-access strategies of experienced [17] D. Morris, M. Ringel Morris, G. Venolia, Search-
web users, in: WWW ’05, 2005. bar: a search-centric web history for task re-
[3] P. Vakkari, A theory of the task-based informa- sumption and information re-finding, in: SIGCHI
tion retrieval process: a summary and generali- ’08, 2008.
[18] W. Du, Z. C. Qian, P. Parsons, Y. V. Chen, Per-
sonal web library: organizing and visualizing
web browsing history, International Journal of in: Proceedings of the 17th ACM conference on
Web Information Systems (2018). Computer supported cooperative work & social
[19] S. Dumais, E. Cutrell, J. J. Cadiz, G. Jancke, computing, 2014, pp. 807–819.
R. Sarin, D. C. Robbins, Stuff i’ve seen: a sys- [34] G. Styliaras, V. Dimou, Teaching of informatics
tem for personal information retrieval and re- (2015).
use, Acm sigir forum (2016).
[20] T. Deng, L. Zhao, L. Feng, W. Xue, Information
re-finding by context: a brain memory inspired
approach, in: ACM CIKM ’11, 2011.
[21] M. Sappelli, S. Verberne, W. Kraaij, Evaluation of
context-aware recommendation systems for in-
formation re-finding, Journal of the Association
for Information Science and Technology (2017).
[22] L. Xu, Z. T. Fernando, X. Zhou, W. Nejdl, Logcan-
vas: visualizing search history using knowledge
graphs, in: ACM SIGIR ’18, 2018.
[23] T. Tolmachova, L. Xu, I. Marenzi, U. Gadiraju,
Visualizing search history in web learning, in:
ICWL ’19, 2019.
[24] C. Shah, R. González-Ibáñez, Exploring infor-
mation seeking processes in collaborative search
tasks, Proceedings of the American Society for
Information Science and Technology (2010).
[25] M. R. Morris, E. Horvitz, Searchtogether: an in-
terface for collaborative web search, in: ACM
symposium on UIST ’07, 2007.
[26] M. Bortoluzzi, I. Marenzi, Web searches for learn-
ing: How language teachers search for online re-
sources., Lingue e Linguaggi (2017).
[27] I. Marenzi, Multiliteracies and e-learning2. 0, Pe-
ter Lang GmbH, 2014.
[28] D. Taibi, F. Bianchi, P. Kemkes, I. Marenzi, Learn-
ing analytics for interpreting., in: CSEDU (1),
2018.
[29] A. Komlodi, G. Marchionini, D. Soergel, Search
history support for finding and using informa-
tion: User interface design recommendations
from a user study, Information processing &
management (2007).
[30] P. C. Blumenfeld, E. Soloway, R. W. Marx, J. S.
Krajcik, M. Guzdial, A. Palincsar, Motivating
project-based learning: Sustaining the doing,
supporting the learning, Educational psycholo-
gist (1991).
[31] L. K. Michaelsen, M. Sweet, The essential ele-
ments of team-based learning, New directions
for teaching and learning (2008).
[32] M. Chau, D. Zeng, H. Chen, M. Huang, D. Hen-
driawan, Design and evaluation of a multi-agent
collaborative web mining system, Decision Sup-
port Systems 35 (2003) 167–183.
[33] R. Kelly, S. J. Payne, Collaborative web search
in context: a study of tool use in everyday tasks,