A Case Study - Using Social Tagging to Engage Students in Learning

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<ul><li><p>8/10/2019 A Case Study - Using Social Tagging to Engage Students in Learning</p><p> 1/7</p><p> A case study: using social tagging to engage students in learningMedical Subject Headings *</p><p>Lauren A. Maggio, MS (LIS), MA, AHIP; Megan Bresnahan, MSI (LIS); David B. Flynn, MS (LIS);Joseph Harzbecker, MSLS, MA, AHIP; Mary Blanchard, MSLS; David Ginn, PhD</p><p>See end of article for authors affiliations. DOI: 10.3163/1536-5050.97.2.003</p><p>In exploring new ways of teaching students how touse Medical Subject Headings (MeSH), librarians atBoston Universitys Alumni Medical Library (AML)integrated social tagging into their instruction. Theseactivities were incorporated into the two-creditgraduate course, GMS MS 640: Introduction toBiomedical Information, required for all students inthe graduate medical science program. Hands-onassignments and in-class exercises enabled librariansto present MeSH and the concept of a controlled</p><p>vocabulary in a familiar and relevant context for thecourses Generation Y student population andprovided students the opportunity to activelyparticipate in creating their education. At theconclusion of these activities, students were surveyedregarding the clarity of the presentation of the MeSHvocabulary. Analysis of survey responses indicatedthat 46% found the concept of MeSH to be the clearestconcept presented in the in-class intervention.</p><p>STATEMENT OF CASE</p><p>The National Institutes of Health defines controlledvocabulary as: A system of terms, involving, e.g.,definitions, hierarchical structure, and cross-referenc-es, that is used to index and retrieve a body of literature in a bibliographic, factual, or other data- base [1]. Perhaps the best-known controlled vocab-ulary is the National Library of Medicines (NLMs)Medical Subject Headings (MeSH), which is used toindex the premier biomedical database, MEDLINE.The use of MeSH is essential for health careprofessionals when they search the biomedical liter-ature [2]. Furthermore, the failure to utilize MeSHwhen searching can be a key reason that a search mayfail [3]. Unfortunately, the concept of a controlledvocabulary, including MeSH, is challenging to teachand difficult to master [2].</p><p>At Boston University Medical Centers AlumniMedical Library (AML), librarians teach the conceptof MeSH and its utility to more than 4,000 patronsannually through the librarys information literacyprogram. During these education sessions, librariansintroduce and demonstrate the use of controlledvocabulary, specifically MeSH, in the context of searching MEDLINE. Librarians explain the structureof the MeSH hierarchy and the indexing processes asthey perform a search. In the majority of thesesessions, students follow along at their own comput-ers, which reinforces the instruction with hands-onpractice. Nonetheless, librarians have struggled toexplain MeSH without resorting to library jargon, andpatrons often have had difficulty understanding andapplying the complicated concept of a controlledvocabulary when searching the biomedical literature.</p><p>The importance of controlled vocabulary in search-ing the biomedical literature led the librarys educa-tion team to revise its teaching strategy by creatingteaching methods to more effectively convey the</p><p>MeSH vocabulary. A majority of the participants inthe librarys education program are in their twenties,and individuals in this age group commonly use Web2.0 innovations, including social tagging [4]. Librari-ans explored how social tagging could supplementinstruction by requiring students to actively partici-pate in the instruction. The librarians chose socialtagging technology as a model because it has beenplaying an increasingly large role in health-relatedprofessional and educational services [5] and it has been found to provide useful tools for positivelyimpacting students information literacy and librari-ans connection with students [6].</p><p>Web 2.0 is broadly defined; Giustini explains that itis an Internet technology trend that encourages thespirit of open sharing and collaboration among users[7]. After discussing various Web 2.0 technologiessuch as wikis, blogs, and mashups, the librarians feltthat instruction on controlled vocabularies could beimproved by incorporating elements of naturallanguage or social tagging. Tagging is the processof creating labels for online content [4] utilized byweb services such as Flickr and Del.icio.us. Twenty-eight percent of Internet users have tagged onlinecontent, and those who are most likely to tag contentare between the ages of eighteen and twenty-nine [4].Therefore, the librarians chose a social taggingbasedexercise to provide a familiar context for students tolearn the MeSH vocabulary. Other connections be-</p><p>tween tagging and controlled vocabulary are presentin the library literature [8], and it has been proposedthat tagging may help engage users in informationmanagement [6, 9].</p><p>BACKGROUND</p><p>In the 2007/08 academic year, librarians at AMLdeveloped and taught the course, MS 640: Introduc-tion to Biomedical Information. MS 640 is a 2-credit,letter-graded course required of all students in themasters of arts in medical sciences degree program</p><p>* Based on a presentation at MLA 08, the 108th Annual Meeting of the Medical Library Association; Chicago, IL; May 19, 2008.</p><p>J Med Libr Assoc 97(2) April 2009 77</p></li><li><p>8/10/2019 A Case Study - Using Social Tagging to Engage Students in Learning</p><p> 2/7</p><p>offered by Boston University School of MedicinesDivision of Graduate Medical Sciences. This coursewas designed by librarians to teach students how tolocate, manage, and add to the biomedical literatureand to prepare students for further education and forhealth care careers. Spanning 14 weeks, the coursewas delivered to 186 students through a combinationof small group and large lecture sections led by 5</p><p>librarian instructors.Significant consideration was given to tailoring thecourse to the students age group. One theme that wasrevisited throughout this curriculum planning wasthe desire to meet students where they are, so thatlibraries and librarians are seen as relevant and become part of their experience [8]. With an averageage of twenty-three, the majority of the students wererecent college graduates and Generation Y members.Based on student demographics and data reported bythe Pew Internet &amp; American Life Project [4], thecourse designers assumed that many of the studentswere likely Web 2.0 users. Librarians hypothesizedthat social tagging would better enable students tounderstand controlled vocabularies. To test thishypothesis, librarians designed teaching plans andassignments using natural language tagging to teachMeSH.</p><p>METHODS</p><p>Pre-class exercise</p><p>After the first session, students were required tocomplete the homework assignment: What wouldyou call it? An exercise in tagging. This assignmenttook students approximately twenty minutes tocomplete and was due before the following in-class</p><p>session. Presented completely online via interactiveforms designed and maintained by the librarys webcoordinator, this assignment presented students withan image, short movie clip, and a MEDLINE article.These digital objects were stripped of identifyinginformation to prevent biasing students with externalinformation. In this study, the librarians focused theirresearch efforts on tracking the students progress intagging just the article. However, students wererequired to tag all three digital objects for theirhomework assignment. Furthermore, as this exercisewas a component of course activities, students wereunaware that this pre-class exercise would be fol-lowed up with a post-class evaluation as a componentof a research project. This research project wasreviewed by the Boston University InstitutionalReview Board (IRB) and deemed in compliance.</p><p>The article selected for the assignment was ahumorous piece from the Canadian Medical Association Journal (CMAJ) that explored how the stomach seemsto expand to make room for dessert during theholidays [10]. This article was selected for its humorand accessibility to students at all levels. Studentswere required to supply 5 natural language tags todescribe each digital object. This assignment account-ed for 5% of the students grades.</p><p>The primary purpose of this assignment was toencourage students to think about the many ways thatdigital objects can be described. The submitted tagsprovided user-generated data that could be used toillustrate inconsistencies and disadvantages of naturallanguage description. In this way, the librarianssought to actively involve learners in their ownconstruction of knowledge [5], which is a powerful</p><p>teaching tool.The assignment was available to the studentsthrough a hypertext markup language (HTML) form.Once students submitted their tags using this form,the data were sent to a table in the librarys MySQLdatabase. Instructors graded the submissions forcompletion. Next, all identifying information in thetable was stripped to anonymize the tags submitted by the students.</p><p>Using Macromedia ColdFusion 8, the web coordi-nator queried tags submitted by students in the table.Duplicate tags were grouped together and counted tocreate a weighted list of terms. Lastly, using cascadingstyle sheets (CSS), the web coordinator assignedlarger fonts and darker colors to tags that had highcounts or frequencies in the table and smaller fontsand lighter colors to those that were few in number.This information was then displayed as a tag cloud.Tag clouds are visual representations of tags, allowingusers to view the various terms used to describe aparticular information object. The number of times anindividual tag was submitted is represented by thesize and color of the tag in the cloud display. Forexample, one tag cloud that was generated from thesubmitted tags describing the article is depicted inFigure 1.</p><p>InterventionOne week after completing the online assignment,students attended a session that introduced MED-LINE using the Ovid interface. Major topics included:NLM indexing, MeSH, Boolean operators, limits, andsearch revision.</p><p>At the beginning of the MEDLINE session, tagclouds corresponding to the three information objectspresented in the assignment were displayed to begin adiscussion about the advantages and disadvantages of using natural language tags. Students were asked tothink about how accurately the large-sized tagsdescribed the article along with possible problemsassociated with this type of description. Three majorpitfalls of relying on natural language tags forsearching were highlighted: synonymy, spelling mis-takes and variations, and specificity [8, 11]. During thediscussion, these problems were contrasted withtraditional indexing using a controlled vocabularysuch as MeSH.</p><p>&amp; Synonymy: As illustrated by the tag clouds,students submitted a wide variety of synonymoustags. For example, funny, humorous, humor,and joke were all tags submitted to describe thearticle. Librarians used this example to demonstrate</p><p>Maggio et al.</p><p>78 J Med Libr Assoc 97(2) April 2009 </p></li><li><p>8/10/2019 A Case Study - Using Social Tagging to Engage Students in Learning</p><p> 3/7</p><p>that many words can describe the same concept andthat these inconsistencies can complicate searching.</p><p>&amp; Spelling mistakes and variations: Dessert wasone of the most common tags used to describe thearticle. However, the spelling mistake desert wassubmitted by more than fifteen students. By high-lighting this common mistake, the librarians wereable to demonstrate the likelihood of misspellingwords using natural language tags, which makessearching more difficult. Variations in US andBritish spellings were also addressed as potentialproblems.</p><p>&amp; Specificity: The tag cloud demonstration alsoallowed librarians to point out that there was greatvariation in the specificity level of submitted tags. Forexample, many students selected broad tags such asdessert to describe the article, whereas severalstudents submitted narrower tags such as blueberrypie, which could prove difficult when attempting tolocate an article.</p><p>The visual presentation and related discussions of the tag clouds took approximately twenty minutes of the MEDLINE session, although the tag clouds andthe tags themselves were referenced throughout thesession. As depicted in Figure 2, the natural languagedescription provided the librarians with a frameworkthat was familiar to students in order to describe theapplication of controlled vocabularies to MEDLINE.A major benefit of this strategy was that it allowed thelibrarians to avoid potentially alienating libraryscience terms, something that has been viewed as an</p><p>ongoing barrier in bibliographic instruction over thepast fifty years [12]. Social tagging tools and vocab-ulary were specifically utilized to explain four majorMEDLINE concepts that had previously been difficultfor the librarians to teach and for students tounderstand:</p><p>&amp; PubMed in-process citations: Librarians utilizedWeb 2.0 vocabulary to describe the relationship of PubMed in-process citations to MEDLINE as citationsthat were waiting to be tagged before being includedin MEDLINE.</p><p>&amp; MeSH Mapping Tool: Using Web 2.0 vocabulary,librarians demonstrated how natural language key-words entered into the search interface were mappedto MeSH terms.</p><p>&amp; Scope Note: As the librarians showed students theMeSH Scope Notes, they pointed out that wordsunder the heading Used For were like naturallanguage tags. Librarians explained that the UsedFor terms represent the variation in natural languagefor the MeSH concept and can be entered into thesearch box to retrieve appropriate MeSH terms.</p><p>&amp; Full Record and Explode: The full-record displaywas described as NLMs structured tag cloud becauseit provided a visual representation of all the tagsthat were selected to describe the article. Thelibrarians also took advantage of this visual repre-sentation to explain that the major or focusterms were akin to the tags that would be larger insize in a more traditional tag cloud, as illustrated inFigure 3.</p><p>Figure 1Tag cloud</p><p>Notice that dessert, one of the most popular tags is displayed in a larger font and darker color due to the high number of times that it was submitted by the students.</p><p>A case study</p><p>J Med Libr Assoc 97(2) April 2009 79</p></li><li><p>8/10/2019 A Case Study - Using Social Tagging to Engage Students in Learning</p><p> 4/7</p><p>Post-class evaluation</p><p>Following the hands-on demonstration of MED-LINE, students completed an online evaluation. Inthis exercise, students retagged the original article.The article was again stripped of any identifyingcitation information to prevent students fromlocating the articles citation and using its relatedMeSH. In contrast to the pre-class exercise wherestudents entered natural language tags, studentssubmitted five MeSH terms that described thearticle. To complete the post-class exercise, studentswere encouraged to use Ovids MeSH mappingtool. The instructors allotted fifteen minutes of classtime for this activity. As with the pre-class exercise,the post-class evaluation was an interactive onlineform that...</p></li></ul>