Paper Title. Computer says no...knowing when

Paper Title. Computer says no...knowing when enough technology is enough! Audience. Educational practitioners Key Themes. New and emerging learning technologies, Classroom tools, Social media and social networking, Virtual and personal learning environments Aims. The paper aims to describe the integration of several technologies into a First Year Foundation Organic Chemistry Module with the specific aims of improving communication, enhancing peer based learning, fostering a community of self-learning and providing the students with a real and virtual spaces to engage with each other and the content both synchronously and asynchronously. A further objective is to provide functional recommendations from practice for those interested in implementing such an approach in their own teaching. Finally, the majority of the technologies discussed are free to use and the paper will outline how these can be applied in other educational environments. Abstract. Engaging first year students in large lectures halls and laboratories can be particularly difficult. Students are exposed to a myriad of distractions, principally technology-based and available through their laptop and smartphones. In this case study, to circumvent these distractions and in an attempt in enhance student engagement, technology was integrated into the learning environment. The various forms of technology were chosen to improve communication, enhance peer based learning, foster a community of self-learning and provide the students with a real and virtual spaces to engage with each other and the content both synchronously and asynchronously. Twitter provided a method of communication between students and the lecturer in the form of an in class back-channel and also a means of rapidly disseminating information to the class. Additional technologies were used, both inside (Clickers) and outside the classroom (PeerWise), in order to prepare the student for the in-class learning activities and also to provide a structured independent and peer-driven learning environment. In this case study it was observed that the in-class technologies were readily and enthusiastically engaged with by the students, however, the outside class technologies were less so. Only the technology that had an assessment weighting associated received continuous student interaction. Post module evaluation noted that, although students welcomed the use of technology in their learning, there was a sense of being overwhelmed with technology and that the students needed space to engage with their different technology based communities; social, personal and educational. In light of this, the paper concludes with suggestions for other practitioners that which to integrate similar technologies into their learning environments. Introduction Students are becoming ever more aware and comfortable with technology (Sharples et al, 2010). It is part of their everyday life, and as such, integration of technology into the classroom is a ‘fait accompli’. Students demand the most interesting and up-to-date

technology as part of their learning (Skiba & Barton, 2006). Research has proven that an engaged student will absorb and understand more, with blended learning (in which technology is seamlessly integrated into the classroom) a key method of student engagement (Johnson & Lillis, 2010). As well as enhancing the learning experience for the student, technology can also be used to reduce the administrative workload on the busy academic in the current environment of large and heterogeneous classes. The case study discussed here outlines the authors’ experiences with integrating and aligning technology in a large, first year foundation organic chemistry class. The main themes discussed are Social media, Engagement and Student responsibility for learning. This is a practice based paper, and therefore focuses on the problems identified in this case study, the subsequent solutions and rationale, how the technology was implemented, and an evaluation of the outcomes. Social Media: Communication with students often reverts to email or a similar messaging system in the virtual learning environment. In this case study Twitter was used to supplement these traditional methods of communication. Twitter is a popular microblogging application that is supported by mobile or desktop devices. It allows registered users to microblog, or simply write succinctly about things that are of interest to them. These microblogs (“Tweets”) are short pieces of information and are restricted to 140 characters per Tweet. Each registered user has a unique username that is preceded by the “@” symbol. Twitter users (“Tweeps”) can choose to receive these Tweets to their Twitter account by “following” the person that interests them. “Following” a person on Twitter means that Tweet posted by the followee will be received by the follower in their Twitter timeline. An alternative way to track specific Tweets is to create a unique identifier (“Hashtag” or #) that is attached to each Tweet. The unique Hashtag can be searched within Twitter and will return only Tweets that contain it. There are alternative search functions within Twitter but these can return no-specific information. Twitter has been described as a combination of personal publishing and communication; where users Tweet not only deliver information, but also to ask questions, seek support and validate ideas (Grosseck & Holotescu, 2008). Tweets, and Twitter, by its very nature is social. Users post, users comment, users re-post, users can engage in private discussion and users can take part in public debates (Krishnamurthy et al., 2008). Twitter is omni-present and users can post anywhere, anytime. The use of Twitter in education is gaining traction as users seek new ways of engaging students in classrooms with ever increasing numbers (Saeed & Sinnappan, 2011). A recent study has summerised the common activities carried out by academic scholars on Twitter; interestingly these scholars broadly fell into the same three categories of non-academic Tweeps, namely sharing information, seeking information and community building (Veletsianos, 2011). In this case study Twitter was used as a quick and simple method of communication with the large cohort class (n=140). Students were made aware of the academics twitter handle (@CBS_Lecturer) and were encouraged to follow the academic. The use of Twitter permitted rapid and effective communication of upcoming topics (e.g. in lectures or laboratories) to all students. Twitter can be employed as an easy way to communicate with students in real time as many Twitter users check their account (appearing as a timeline of tweets) on a mobile device. If students did not want to follow the academic on Twitter they could track class specific Tweets by searching the class Hashtag. In this case study the author used the class module code as the unique Hashtag as this is easily remembered and relevant

to the students. The unique Hashtag was also used in class to crowd source questions, comments or ideas from the student group, particularly in large lecture halls. This back channel source of information can be monitored by the academic at specific times during the class and items Tweeted discussed “on the fly”. This approach allows students to engage with the academic no matter the size of the room and aids student buy-in to class participation. A simple application of crowd sourced Tweets could be the generation of a “tweet cloud”. Akin to a word cloud, the tweet cloud can collate words (or topics) supplied by the student cohort on, for example, the areas of confusion before and after a lecture. This is a quick and very visual representation of student understanding and is particularly effective in large classes. Within higher education Twitter can be incorporated as an engaging teaching and learning tool; other examples currently used by the author include: Twitter-based fora. This online forum where one moderator (the academic or selected student) guides the discussion, based around tweets, over the course of one hour. It can be very fast paced, as tweets are not regulated and the only commonality is the discussion hashtag. These discussions, also known as crowd sourcing are commonly used at edtech conferences; however, the discussion can be opened and the opinion of hundreds of people can be gauged in real time from their tweets. The quantity and speed at which the tweets are landing can be off putting and disorientating for some users; often times taking away from the key point of the forum. Prenzky’s (2001) view on ‘edutainment’ can be directly related to this type of Tweeting when, for example, debate shows or educational programmes are pre-empted by the programme’s hash tag to allow the community to discuss in real time the contents of the show. Online e-tivity: An online e-tivity could be used as part of an initial socialisation tasks in line with Salmons’ (2002) five stage model for eLearning activities. Students begin the activity by working individually and selecting a relevant person on Twitter to follow. A relevant person would be someone who posts regularly on items that relate to a topic relevant to the module/topic in question. If required, the tutor can administer a class account and (s)he can in turn follow each student to monitor whom each student is following and provide assistance during the initial phase of this work. Students can interact with each other, the tutor and experts in the area via the Twitter “@username” approach. The student then creates a brief summary of important Tweets from their Tweep once the student has followed their Tweep for a number of days (or trawled their previous Tweets). This summary is then circulated to their group for review or posted to the groups Wiki on the Virtual Learning Environment. Once summaries from all students have been posted to the groups’ wiki, the group will then analyse and evaluate the suite of Tweeps collected by the individual members and create a priority list of Tweeps in the relevant area. Part of this prioritization will include a rationale, based on the group online discussion. Higher order, critical thinking should be encouraged during discussion and prioritisation. There are several beneficial outcomes from this initial e-tivity including; students becoming more comfortable working with each other in an online environment, the class identifying relevant Tweeps to follow and the class is introduced to use of Twitter as a Personal Learning Network.



Dissemination and Personal Learning Network: The author currently uses Twitter as a method of personal publication and dissemination of ideas. As the character limit is small, the Tweet can contain a weblink to a further body of work, perhaps a website or cloud-hosted file. The author also employs Twitter as a Personal Learning Network to follow peers that Tweet regularly in relevant areas. Refinement of suitable Tweeps to follow can take some time; however, the benefit of regular, insightful and timely ideas relevant to your area of interest is worth the initial effort.

Engagement The use of Clickers in this case study in engaging students will be discussed as an example of technology integration to enhance student engagement. Clickers can provide a simple way in which to generate an atmosphere of student interaction that can simultaneously enhance engagement, critical thinking and problem solving amongst groups and individuals. Clickers can also provide an immediate source of feedback for the academic and student, rapidly identifying areas of mis-understanding (Morredich & Moore, 2007). Previous researchers investigating the use of Clickers have cited the enthusiastic response of students towards Clickers (Caldwell, 2007) and also the potential improvements in student learning based on Clicker use (Beatty et al., 2006). More specifically, educationalists who have used Clickers effectively in the classroom have reported improved student interaction (Weerts, 2009), engagement (Mayer, 2009), active-learning, participation, and an increased level of advance preparation (Cook & Hazelwood, 2002). Clickers are most commonly used in large classes; however they can also be used, with care and as in this case study, in the laboratory. Clickers can provide an immediate and tangible change to the way the students currently engage with the laboratory session. Clickers can be integrated at every level of the laboratory as outlined below. The descriptions below outline how Clickers were used during this case study; although not a requirement, the continual use of Clickers during all stages of the laboratory is encouraged as the students see the Clickers as a central part of their lab as opposed to a ‘bolt on’ use of technology for the sake of it. Before the lab: At the beginning of lab, Clickers can be used to ascertain the level of understanding of the group prior to the laboratory session. A short set of questions can focus around the key learning objectives for the particular session at hand, and the instant responses obtained from the Clickers can indicate if the students were familiar with their goals. [e.g. “Why is method A used?”, “Which of these methods (B, C, D, E) is a viable alternative?”, “What is the expected outcome from today’s experiment?”]. Other pertinent areas, such as appreciation of safety concerns, could be investigated through simple Clicker responses. In this way, the academic can ensure all students are suitably prepared for the laboratory session; through an engaging, and quick, student-friendly task. Students can form small groups of two or three if there are more students than Clickers; the small groups then discuss the question and submit an agreed consensus answer. During the lab:

During the lab, the Clickers could be used to capture group data generated during the experiments For example; “What was your groups’ percentage yield after crystallisation?” (select 1 for 8 >9 >10 11 % students 10 7 2 2 1 Q’s answered >20 >40 >60 >80 >100 % students 48 28 28 23 18 Table Two: Breakdown of the assessment weightings for the case study module. The module was a foundation organic chemistry module; the primary learning outcomes focussed on students’ ability to recognise, name and predict basic organic chemistry functional groups and reactions in both theory and laboratory based practice. Element % Module Weighting Laboratory Reports (x4) 6.25 Laboratory Skills Exam and Report 25 Term-time Small Stakes MCQs (x3) 7 End-of-Term Large Stake MCQ (x1) 25 PeerWise engagement 4

Figure One: Plot of the number of questions contributed and the number of questions answered during the fourteen week long semester. The three term-time small stake MCQs and one high stake MCQs are overlaid. The students had a one week window to complete the small stakes MCQs at a time and location of the students’ choice; whereas the high stake MCQ was carried out at a defined time and location for all students.









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