This week has been a week of reflection and interpretation. After considering my trepidations and fear during week 1, I have encountered a period of time where an impossibility becomes a reality. The last 10 weeks has been both exciting but draining and I’m thankful for the EDC community in their support and discussions that have challenged my thought process and learning journey. As a reflection of last weeks topic on ‘Learning Analytics’ I created my own infographic to provide a visualisation of LA within my field and appreciate the backstage discussions with peers. I valued online educational tools used by dance companies such as Scottish Ballet here, here,here and here. I valued the influence technology has on my child’s love for anatomy. I enjoyed the wonderful Wayne McGregor delivering a TED talk as he describes the body as the most technically literate thing that we have. I considered the affect of algorithms on young dancers using YouTube to gain instantaneous results in their technique and valued dance pioneers using social media to distribute the right message of Health and Wellbeing as well as Injury Prevention. I also liked a video on youtube which promotes new technology that uses learning analytics to create specialised programs for participants with additional support needs. Following the topic of ‘Algorithms’ in week 8 Coursera sent me an e-mail with course recommendations which made me questions potential student decisions when algorithms are at play. After the Tweetorial, I used Mind Mup to create a Mind Map and shared using Evernote. I then finalised the week by completing this weeks task which asked us to analyse the data provided by the Tweetorial Archive.
Last week it was course requirement to participate in a Tweetorial set up by the EDC tutors Jeremy Knox and James Lamb. Unfortunately, it so happened to be the week that I was overwhelmed with work commitments. I spent days wondering how I was going to juggle everything but now that it is over I can look back and it doesn’t seem so intimidating. I managed to follow the online activity whilst at work under assessment conditions but only when taking a break from my duties which were short and sporadic. I finally made a contribution to the tweetorial but only at the very last hour. I calculated that I actually spent hours reading, contextualising and navigating my way through the #mscedc hashtag over the two day period but felt disappointed that I wasn’t able to contribute in an impactful manner. I instead felt like the full stop or a bookend to the conversation to which Dirk highlights in his analysis.
This week our task was to look at the data collected within the Tweetorial archive and participate in a Google hangout to discuss our findings and perspectives. As per usual the conversation was dominated by the more confident students. Now, I say confident lightly, do they merely have less inhibitions and are they less assertive or interested in the perception of other participants? Whether active or passive the learning environment can be perceived from ones position. A passive participant can engage in conversation by listening and observing with confidence whilst an active participant is more vocal and willing to share their opinions and findings. Many times whilst scrolling through the Tweetorial I found myself asking questions to my peers through direct messages and wondered if I should ‘reveal’ myself by commenting on the public forum. With limited time and, if I’m honest, a confused outlook on the fragmented comments I felt pressure to comment in a qualitative way. I therefore settled for ‘likes’ until I had the appropriate time and understanding.
When looking at the data, the EDC participants were ranked in a Top Ten list of contributors based on the number of tweets they posted. Were the others as engaged but less vocal online? Did the conversation on cheese and roller skates which took up a portion of the Tweetorial help build the stats? The questions proposed by Jeremy and James initiated conversation but an in depth discussion was lacking in the presentation of 140 characters. At times, I questioned some of the conversations that took place and wondered if they learned something new or if they were merely showing their existing knowledge and understanding? The archive demonstrates the activity by the number of tweets from each participant, the increase in activity over the tweetorial period, top words, source of tweets and the users mentioned. Although the data is steady in numbers, it does not reflect the learning or educational value of the task. The environment, availability and activity (work or social) of each participant was not taken into account. A participant at lunch with friends, at work with colleagues, looking after children or even sneaking a peak at the twitter activity on their toilet break (dipping in and out of focus) is not accurately measured. We could use the ‘source of tweets’ to measure this but even if participants were on Tweetdeck at work , work commitments could also cause distractions. Conversations mainly took place during the day (GMT) and participants located within a different timezone were engaged at different time periods which may have had an affect on focus, energy levels and engagement. Did time affect the pattern of engagement in conversation? Although, I do have to say, Philip managed pretty well with his online activity and was ranked the ‘Top number of Tweets’ award. I think he may have pulled an all nighter and survived on red bull 😉
The ranking of participants within the Tweetorial archive provides a competitive environment. Will this have an impact on the EDC group where the community of learners use online forums as a provision of support and discussion? The ranking could create issues in regard to self-efficacy and motivation. Unless the participant is able to assess the data provided and value their learning experience there is a danger one may change their habits or become demotivated. Online ‘activity’ is different when compared to what that participant is processing or what they understand. If we were to revisit the Tweetorial would participants tweet to show their understanding? Or would they tweet inappropriate and multiple tweets to improve the number of posts? Would their behaviour change if they knew what was being measured?
Once I found time to contribute to the Tweetorial, I tried to capture my point in a limited number of tweet, sometimes using a hypothetical question as I knew my tweet may go unanswered. I knew that most participants had left the ‘party’ which influenced the tone of my tweets. I also didn’t want to repeat what most had already mentioned. I felt the repetition unnecessary and the tweet invalid to my learning seen as I had already considered the aspect due to my peers contribution. Although late to the party I had copious amounts of posts to sift through and digest, what I retained is not recorded and therefore not valid if only assessing the data. I also found it difficult to tag/mention all participants of a particular conversation due to the number of characters left. I instead replied directly to the lecturer, was this experienced by others? If so, could this have influenced the data that measured the users mentioned?
Had I known the Tweetorial objectives and the data measured would I have changed my behaviour? Unfortunately, I was in a situation that restricted access to wifi and my smartphone. I may have ‘revealed’ myself earlier but the quality of my contribution would have been low and I don’t think I would have changed my understanding until looking over the conversations in depth. I also understood my habitual learning process and that the observations would be more productive than idle chat.