It is well established that increasing physical activity will increase heart rate, however there have been substantial amounts of study into the variability of HR in relation to cognitive activity and stress (PérusseLachance, 2012). HR is the peripheral measure most used to assay affect and cognition (Guerra, 2015). As far back as the 1970s a series of experiments by Lacey (1970) and Lacey et al (1974) demonstrated that tasks requiring increased cognitive processing are associated with HR acceleration. Numerous experiments have been conducted measuring HR and cognitive tasks, including a reported increase in HR for computer gamers performing complex gaming tasks and by subjects performing difficult mental arithmetic (Turner & Carroll, 1985). Abundant real world occupation studies have reported HR increases due to increased physical and cognitive task load, such as for air traffic controllers (Wilson & Eggemeier, 1991), fighter pilots (Wilson, 1993), miners (Montoliu, 1995) and professional musicians (Iñesta, 2005). There have been some educational based studies including a limited number of studies in the use of HR as a measure of student cognitive engagement in university lectures. Bligh carried out a series of classroom lecture studies showing that student HR decreased over the course of a 50minute lecture (Bligh 1972, 1998, 2000). The decline in HR was interpreted as a measure of decreasing arousal, which Bligh considered as one component of cognitive engagement. Buchheit (2010) presented the HR profile of a student presenting his PhD, and showed that stress was likely to be very high at the start of the talk (as inferred from his HR reaching 87% of maximal values), but decreased continuously as the presentation progressed. Several HR peaks occurred with the toughest questions raised by the examiners. While there are some HR studies of public speakers there have been surprisingly very few studies carried out in relation to university lecturers during a lecture. In one of the very few, Filaire (2010) conducted a study that involved the collection of beatbybeat HR data of lecturers before and immediately after a two hour lecture. It concluded that there was generally an increase in the lecturer’s HR as recorded immediately after the lecture compared to the prelecture recording. Filaire then linked the increase, in conjunction with measured stress markers in the lecturer’s saliva, as evidence of increased stress. Remarkably there are no known studies that accurately track lecturer HR activity during the lecture. The recent proliferation of accurate, cheap and unobtrusive wearable devices with biometric sensors presents a new opportunity to perform a relatively inexpensive, natural, large scale study on the HR patterns of lecturers during lectures. Objectives stages General HR patterns during the lecture: The initial objective was to use wearable devices (Microsoft Band 2) to measure and record the HR of lecturers during a number of lectures and analyse the data to seek to identify any general patterns in HR during the length of the lecture. HR and teaching activity: The objective was to analyse the HR data to seek to identify and potentially link repeatable HR patterns to the teaching activities of the lecturer during the lecture, such as presenting, demonstrating or answering difficult questions. HR and potential influencing factors: The objective was to analyse how HR is affected by potential influencing factors, such as complexity of material being taught, the numbers of students attending, the time of day, how prepared the lecturer was, how familiar the lecturer was with the taught content, the amount of active learning within the lecture, how well the lecture slept the previous night, prelecture anxiety and general wellbeing.
|Number of pages||4|
|Publication status||Published - 25 Aug 2017|
|Event||ECER 2017 - Copenhagen, Denmark|
Duration: 22 Aug 2017 → 25 Aug 2017
|Period||22/08/2017 → 25/08/2017|
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Learner analytics of student programmers: The use of innovative technologies to better understand the learning behaviours of student programmersAuthor: McGowan, A., Dec 2021
Student thesis: Doctoral Thesis › Doctor of PhilosophyFile