Teachers’ and tutors’ social reflection around SenseCam images

https://doi.org/10.1016/j.ijhcs.2009.09.004Get rights and content

Abstract

As photographic technologies continue to develop, so too do the social practices surrounding their use. The focus of this paper is on the social practices surrounding images captured from a new photographic device—SenseCam—which, rather than capturing individual images when triggered by the user, automatically captures a series of images. This paper is concerned with the use of SenseCam digital images in social contexts where there is a professional purpose—supporting the collaborative reflective practices of school teachers and university tutors as part of their professional development. Analysis of video data collected from 16 in-situ case studies of reflective discussions shows evidence that reflection took place as defined in the literature. Further the phototalk around SenseCam images was found to benefit reflection in these social situations through promotion of a rich shared understanding of the lesson context: supporting return to the experience, sharing of background context, grounding conversations, illustrating and providing evidence, and allowing people to see more. The paper concludes with a discussion on how different features of SenseCam images, such as variable quality, lack of audio and incompleteness, helped in this reflection or not. Finally implications from this work and participant's comments are used to suggest ways in which SenseCam may be used in the future in teachers’ and tutors’ social reflection.

Introduction

With advances in digital photography there has been a growing interest in the novel ways in which photos are brought into social practices and the ways in which people are evolving their photographic habits. Whilst most of this work is focussed on the digital form of the still camera, a different type of digital photo is emerging in the sphere of life-logging.

SenseCam is a prototype life-logging device currently under development at Microsoft Research in Cambridge (e.g. Williams and Wood, 2004; Cherry, 2005). It is a small wearable device combining a digital camera with a number of built-in sensors and is made to be worn by persons around their neck like a pendant (see Fig. 1). The sensors, which measure light, motion, sound, infra-red and ambient temperature, are used to trigger digital still images to be taken at ‘good’ times when something interesting may be happening. Currently ‘good’ is defined by the developer as the time when there is a sudden change in light (which might happen when we move from one room to another), sound or temperature, or when the infra-red data combined with motion detection suggest another person is nearby. On average three or four photos per minute are triggered in this way. The camera also has a very wide-angle, fish-eye lens that captures most of what is the field of view of the wearer from a first-person perspective (see Figs. 2–7 for example images). These combined features allow the wearer to passively capture a whole day's worth of images without having to press a trigger or aim the camera, leaving their hands and attention free to get on with their everyday tasks. When downloaded to a PC the images can be viewed using a rapid serial visualization tool, playing somewhat like a sped-up movie, and the whole day may take only around 10 min to review. In this way, SenseCam can be considered as a ‘life-logging’ tool.

Much research to date with SenseCam has focused on its potential to record life experience as a support to memory—indeed it has been shown to be an effective tool in supporting people with severe memory-loss (Cherry, 2005), and to support different aspects of ‘remembering’ and ‘knowing’ for people with a normal memory (Sellen et al., 2007). More recently research has suggested that SenseCam images can also evoke reflection on past life experiences (Harper et al., 2008, Harper et al., 2007) and that sharing such images with others prompts reflection on own and others’ lives (Lindley et al., 2009). The focus of this research has been very much on everyday life—the way SenseCam as a life-logging tool was envisaged to be used. We have also shown that SenseCam can support reflection in a learning context where students used the images from a field trip to reflect on their experiences (Fleck and Fitzpatrick, 2006).

In this paper, however, we consider the value of SenseCam images in a work setting: we explore the potential of the device to capture aspects of professional experience and share these with others, espoused as part of being a good reflective practitioner (Moon, 1999). The professional practice we focus on is that of teaching—in both school and university contexts. This is a domain in which another visual experience-recording technology, video, has been advocated for over 30 years (Zuber-Skerritt, 1984). We have previously undertaken research with individual school teachers and university tutors using SenseCam for self-reflection and have shown it to be useful (Fleck, 2008). Here we expand on these findings and focus on how SenseCam might be used in schools and universities to support reflection in social contexts; specifically we look at how it can support reflective practice conversations between novice teacher peers, novice teachers and their mentors, and between trainee university tutors.

Section snippets

Teachers’ reflective practice

Reflective practice, inspired by the work of Schön (1983), is a key element of professional practice for teachers and tutors and described as a ‘main mission’ (Manouchehri, 2002) of teacher training. Schön's core idea is that in certain professions such as teaching, nursing or social work, where a practitioner will often have to deal with real-world messy situations that cannot easily be mapped onto a professional rule book for action, professionals can, over time, learn to function very well.

Methodology

This research takes a case study approach. The cases on which this paper is based form part of a larger body of research to understand the space of possibilities for how SenseCam might support the self and social reflective practice of teachers and tutors in a variety of situations. The 16 cases discussed here (see Table 1) are the social reflection cases in which trainee teachers and tutors reflect alongside their peers or supervisors. All sessions were carried out within the constraints of

Findings

The coding of the data against the reflection framework showed that reflection was taking place; whilst much of the conversation could be considered as non-reflective description, in most cases more than half of the conversation reached a level of at least R1 and included chunks classified as R2 level reflection. Such a balance of descriptive and reflective talk is in line with findings from other research (Hatton and Smith, 1995). Having established that reflection occurred, further analysis

Discussion

Given the recognised value of video and still images for reflection, we were interested to see how a new type of imaging technology, SenseCam, with its passively collected series of images, might support social reflection for teachers and tutors. Coding of discussion chunks shows that reflection clearly occurred in the sessions. Further analysis of those chunks suggests that SenseCam images played a role in the discussions, which were not unlike types of ‘phototalk’ already described in the

Acknowledgements

This research was funded by an EPSRC studentship as part of the Equator IRC Project (www.equator.ac.uk) funded by EPSRC Grant no. GR/N15986/01. The SenseCams were provided by Microsoft Research in Cambridge, UK.

References (38)

  • Clark, H.H., Brennan, S.E., 1991. Grounding in communication. Perspectives on socially shared cognition. In: Resnick,...
  • S.T. Collier

    Characteristics of reflective thought during the student teaching experience

    Journal of Teacher Education

    (1999)
  • C. Conati et al.

    Generating tailored examples to support learning via self-explanation

  • A. Crabtree et al.

    Collaborating around collections: informing the continued development of photoware

  • Dillenbourg, P., 1999. What do you mean by ‘collaborative learning’? Collaborative learning: cognitive and...
  • Fleck, R., 2008. Exploring the potential of passive image capture to support reflection on experience. D.Phil. Thesis,...
  • Fleck, R., Fitzpatrick, G., 2006. Supporting collaborative reflection with passive image capture. In: Proceedings of...
  • D. Frohlich

    Audiophotography: Bringing Photos to Life with Sounds

    (2004)
  • Harper, R., Randall, D., Smyth, N., Evans, C., Heledd, L., Moore, R., 2008. The past is a different place: they do...
  • Cited by (54)

    • Multimodal joint learning for personal knowledge base construction from Twitter-based lifelogs

      2020, Information Processing and Management
      Citation Excerpt :

      Most of the previous work on life event extraction focuses on either image-based lifelogs from wearable cameras or text-based lifelogs on the social media platforms. In recent years, the visual lifelogs, captured through the devices such as Sensecam (Hodges et al., 2006) and Narrative (Kallstrom, 2013), have been investigated in a variety of applications including aiding human memory recall (Harrell, 2010; Hodges et al., 2006; Woodberry et al., 2015), healthcare (Kerr et al., 2013; Mohan, Lee, Jaichandar & Calderon, 2012; O'Loughlin et al., 2013), diet monitoring (Maekawa et al., 2013; Nohara, Kotsuka, Hashimoto & Horiuchi, 2010), informing one's lifestyle change, and self-reflection (Fleck et al., 2009; Harper et al., 2008). Gurrin et al. (2016) release personal lifelog data of three lifeloggers for the NTCIR12-Lifelog task which are logged by wearable camera for a period of about one month.

    • Multimodal Analytics for Collaborative Teacher Reflection of Human-AI Hybrid Teaching: Design Opportunities and Constraints

      2023, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    View all citing articles on Scopus
    View full text