Augmenting Autobiographical Memory: an Approach Based on Cognitive Psychology
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Augmenting Autobiographical Memory: An Approach Based on Cognitive Psychology A thesis submitted in fulfilment of the requirements for the degree of Doctor of Philosophy in Computer Science at The University of Waikato by Andrea Schweer Department of Computer Science Hamilton, New Zealand 2011 © 2011 Andrea Schweer Dedicated to the memory of Liesel Schweer née Maas Abstract This thesis investigates how an interactive software system can support a person in remembering their past experiences and information related to these experiences. It proposes design recommendations for augmented autobiographical memory systems derived from Cognitive Psychology re- search into human memory – a perspective missing from prior work. Based on these recommendations, a conceptual design of an augmented autobiographical memory system is developed that aims to support users in retrieving cues and factual information related to experiences as well as in reconstructing those experiences. The retrieval aspects of this de- sign are operationalised in an interactive software system called the Dig- ital Parrot. Three important factors in the design and implementation are the context of an experience, semantic information about items in the system and associations between items. Two user studies evaluated the design and implementation of the Dig- ital Parrot. The first study focused on the system’s usability. It showed that the participants could use the Digital Parrot to accurately answer questions about an example memory data set and revealed a number of usability issues in the Digital Parrot’s user interface. The second study embodied a novel approach to evaluating systems of this type and tested how an improved version of the Digital Parrot supported the participants in remembering experiences after an extended time period of two years. The study found that the Digital Parrot allowed the participants to an- swer questions about their own past experiences more completely and more correctly than unaided memory and that it allowed them to answer questions for which the participants’ established strategies to counteract memory failures were likely to be unsuccessful. In the studies, associations between items were the most helpful fac- v tor for accessing memory-related information. The inclusion of semantic information was found to be promising especially in combination with textual search. Context was used to access information by the partici- pants in both studies less often than expected, which suggests the need for further research. Identifying how to appropriately augment autobiographical memory is an important goal given the increasing volume of information to which users are exposed. This thesis contributes to achievement of this goal by stating the problem in Cognitive Psychology terms and by making design recommendations for augmented autobiographical memory systems. The recommendations are confirmed by the design and implementation of such a system and by empirical evaluations using an evaluation method appropriate for the field. vi Acknowledgements First of all I thank my two main supervisors, Annika Hinze and Steve Jones. Together and individually, you provided a mix of inspiration, en- thusiasm, constructive criticism, encouragement and reassurance. I am grateful for this opportunity to grow both as a person and as a researcher. Many thanks also to Ian Witten, the third member of my supervisory panel. I also thank everyone who discussed my research with me, in the Com- puter Science department and at conferences. In particular I’d like to thank Dave Nichols, Angela Martin and Judy Bowen. Past and present members of the ISDB group throughout the years provided constructive criticism and opportunities for discussion; thank you all. Thanks to Stefan Mutter, Judy Bowen and Andreas Löf for proofreading parts of this thesis. Thanks go to everyone working behind the scenes who ensured that I could conduct and write up the research presented in this thesis without major hang-ups, in particular Clint Dilks and the secretaries. I am very grateful for the friendship with, and support from, current and former fellow PhD students in the Computer Science department. Special mention to Andreas Löf, Matt Jervis, Simon Laing, David Milne, Kathryn Hempstalk and Doris Jung. And an extra-special mention to Ste- fan Mutter, without whom this thesis wouldn’t be what it is – nor would I be who I am now. Other friends, in the department and further away, deserve my grat- itude, for things as different as feeding me (special mention: Tim and Jacqui Elphick), distracting me (everyone with whom I went climbing or played recorders, boardgames or video games), asking me how my thesis was going and not asking me how my thesis was going. My thanks go to vii you all. Particular thanks go to Katrin Credner for supporting me from the other end of the world, sending the occasional care parcel and gen- erally putting things into perspective. Thanks also go to the various sup- portive flatmates I’ve had while working on my PhD, particularly Petra Malik and Briar Paul. My family, especially my father Wolfgang Schweer, my mother Ulrike Engelsing and my aunt Bärbel Schweer, supported me in many small and big ways and also have my gratitude. Finally, I cannot thank Andreas Löf enough for all his support through- out the years and in particular for coping (“well, but not too well”) with my all-but-absence in the weeks leading up to the submission of this the- sis. I owe you – and I’m sure you’ll have plenty of opportunities to collect when it’s your turn to write up! I gratefully acknowledge the financial support of the Computer Science department at the University of Waikato. Further financial support came from Google Australia/NZ in the form of the Anita Borg Memorial Schol- arship in 2008. My sincere thanks to all participants in the user studies I conducted for my PhD research. viii Contents 1 Introduction 1 1.1 Research agenda ........................ 1 1.1.1 Objective ......................... 2 1.1.2 Research questions ................... 2 1.2 Structure of this thesis ..................... 6 2 Augmenting memory: a Cognitive Psychology perspective 9 2.1 Formation and types of memories ............... 11 2.1.1 Long-term memory ................... 12 2.1.2 Autobiographical memory ............... 13 2.1.3 Concepts, scripts and schemata ............ 16 2.1.4 Memory for planned actions .............. 17 2.2 Remembering .......................... 18 2.2.1 Recollections ....................... 18 2.2.2 Cues and process .................... 19 2.3 Memory failures ......................... 21 2.3.1 General memory ..................... 22 2.3.2 Autobiographical memory ............... 25 2.4 Discussion ............................ 26 2.4.1 Definition of terms .................... 26 2.4.2 Related design approaches ............... 28 2.4.3 Recommendations .................... 29 2.5 Summary ............................. 34 ix Contents 3 Augmenting memory: a Computer Science perspective 37 3.1 Focus ............................... 37 3.1.1 Scope ........................... 37 3.1.2 Criteria .......................... 38 3.2 Continuous archival and retrieval of personal experiences 39 3.2.1 Systems .......................... 40 3.2.2 User studies ....................... 48 3.3 Personal Information Management .............. 50 3.3.1 Systems .......................... 51 3.3.2 User studies ....................... 59 3.4 Discussion ............................ 65 3.4.1 Type of remembering .................. 65 3.4.2 Type of information ................... 66 3.4.3 Phase ........................... 66 3.4.4 Context .......................... 67 3.4.5 Semantic information .................. 67 3.4.6 Associations ....................... 68 3.5 Summary ............................. 68 4 Conceptual design of an augmented memory system 71 4.1 Focus ............................... 72 4.1.1 Targeted situations ................... 72 4.1.2 Links to related work .................. 75 4.2 Conceptual architecture .................... 76 4.2.1 Experiencing ....................... 76 4.2.2 Revising .......................... 77 4.2.3 Remembering ...................... 78 4.3 Requirements .......................... 78 4.3.1 Overall system ...................... 79 4.3.2 User interface ...................... 79 4.3.3 Capture component ................... 80 x Contents 4.3.4 Data model and storage ................. 80 4.4 Interaction examples ...................... 80 4.4.1 Sarah the Earth Sciences lecturer ........... 81 4.4.2 Sarah stores a conversation at a field trip ...... 82 4.4.3 Sarah tries to remember a conversation ....... 83 4.4.4 Eric the Maths PhD student .............. 84 4.4.5 Eric takes notes at a conference talk ......... 84 4.4.6 Eric tries