Vassilis Kostakos
Biographic Data
| ID | 4972875 |
|---|---|
| NAME | Vassilis Kostakos |
| GIVEN NAMES | Vassilis |
| FAMILY NAME | Kostakos |
| SIGNATURE | KOSTAKOS V |
| AFFILIATIONS | The University of Melbourne |
| ORCID | 0000-0003-2804-6038 |
| VERIFIED | Yes |
| TOTAL WORKS | 15 |
| TOTAL CITATIONS | 17 |
| AUTHOR COUNT | 15 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2014 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
From prediction to explanation
Smartphones are essential to daily life, and their rich data streams have been used to study how people use their phones, and more broadly human behaviour. While previous research has largely focused on app usage and keystroke dynamics to predict smartphone use, these analyses are typically limited to making predictions rather than providing explanations or reasoning for observed behaviours. In this exploratory study, we investigate the potential…
Unpacking Instagram use
“Instant Happiness”
Mapping 20 years of accessibility research in HCI
Emotion trajectories in smartphone use
Information flow and cognition affect each other
In the context of learning systems, identifying causal relationships among information presented to the user, their behavior and cognitive effort required/exerted to understand and perform a task is key to building effective learning experiences, and to maintain engagement in learning processes. An unexplored question is whether our interaction with presented information affects our cognitive effort (and behaviour), or vice-versa. We investigate …
Quantifying determinants of social conformity in an online debating website
Fitbit for learning
The assessment of learning during class activities mostly relies on standardized questionnaires to evaluate the efficacy of the learning design elements. However, standardized questionnaires pose additional strain on students, do not provide “temporal” information during the learning experience, require considerable effort and language competence, and sometimes are not appropriate. To overcome these challenges, we propose using wearable devices, …
Overcoming compliance bias in self-report studies
Modeling interaction as a complex system
Researchers in Human-Computer Interaction typically rely on experiments to assess the causal effects of experimental conditions on variables of interest. Although this classic approach can be very useful, it offers little help in tackling questions of causality in the kind of data that are increasingly common in HCI – capturing user behavior ‘in the wild.’ To analyze such data, model-based regressions such as cross-lagged panel models or vector a…
Impact of contextual and personal determinants on online social conformity
Avoiding pitfalls when using machine learning in HCI studies
Machine Learning (ML) has come of age and has revolutionized several fields in computing and beyond, including Human Computer Interaction.Historically, human subjects studies have adopted ML techniques for more than a decade, for example for activity recognition and wearable computing.However, there now exists a plethora of application domains where ML approaches are enriching interactive computing research.Here, we wish to highlight some of the …
Facilitating Collocated Crowdsourcing on Situated Displays
Online crowdsourcing enables the distribution of work to a global labor force as small and often repetitive tasks. Recently, situated crowdsourcing has emerged as a complementary enabler to elicit labor in specific locations and from specific crowds. Teamwork in online crowdsourcing has been recently shown to increase the quality of output, but teamwork in situated crowdsourcing remains unexplored. We set out to fill this gap. We present a generi…
The big hole in HCI research
column Share on The big hole in HCI research Author: Vassilis Kostakos University of Oulu University of OuluView Profile Authors Info & Claims InteractionsVolume 22Issue 2March + April 2015 pp 48–51https://doi.org/10.1145/2729103Published:25 February 2015Publication History 37citation2,744DownloadsMetricsTotal Citations37Total Downloads2,744Last 12 Months393Last 6 weeks57 Get Citation AlertsNew Citation Alert added!This alert has been successfull…
An empirical investigation of mobile government adoption in rural China
An empirical investigation of mobile government adoption in rural China
The big hole in HCI research
column Share on The big hole in HCI research Author: Vassilis Kostakos University of Oulu University of OuluView Profile Authors Info & Claims InteractionsVolume 22Issue 2March + April 2015 pp 48–51https://doi.org/10.1145/2729103Published:25 February 2015Publication History 37citation2,744DownloadsMetricsTotal Citations37Total Downloads2,744Last 12 Months393Last 6 weeks57 Get Citation AlertsNew Citation Alert added!This alert has been successfull…
Avoiding pitfalls when using machine learning in HCI studies
Machine Learning (ML) has come of age and has revolutionized several fields in computing and beyond, including Human Computer Interaction.Historically, human subjects studies have adopted ML techniques for more than a decade, for example for activity recognition and wearable computing.However, there now exists a plethora of application domains where ML approaches are enriching interactive computing research.Here, we wish to highlight some of the …
Facilitating Collocated Crowdsourcing on Situated Displays
Online crowdsourcing enables the distribution of work to a global labor force as small and often repetitive tasks. Recently, situated crowdsourcing has emerged as a complementary enabler to elicit labor in specific locations and from specific crowds. Teamwork in online crowdsourcing has been recently shown to increase the quality of output, but teamwork in situated crowdsourcing remains unexplored. We set out to fill this gap. We present a generi…
Fitbit for learning
The assessment of learning during class activities mostly relies on standardized questionnaires to evaluate the efficacy of the learning design elements. However, standardized questionnaires pose additional strain on students, do not provide “temporal” information during the learning experience, require considerable effort and language competence, and sometimes are not appropriate. To overcome these challenges, we propose using wearable devices, …
Overcoming compliance bias in self-report studies
Modeling interaction as a complex system
Researchers in Human-Computer Interaction typically rely on experiments to assess the causal effects of experimental conditions on variables of interest. Although this classic approach can be very useful, it offers little help in tackling questions of causality in the kind of data that are increasingly common in HCI – capturing user behavior ‘in the wild.’ To analyze such data, model-based regressions such as cross-lagged panel models or vector a…
Impact of contextual and personal determinants on online social conformity
Information flow and cognition affect each other
In the context of learning systems, identifying causal relationships among information presented to the user, their behavior and cognitive effort required/exerted to understand and perform a task is key to building effective learning experiences, and to maintain engagement in learning processes. An unexplored question is whether our interaction with presented information affects our cognitive effort (and behaviour), or vice-versa. We investigate …
Quantifying determinants of social conformity in an online debating website
Emotion trajectories in smartphone use
“Instant Happiness”
Mapping 20 years of accessibility research in HCI
Unpacking Instagram use
From prediction to explanation
Smartphones are essential to daily life, and their rich data streams have been used to study how people use their phones, and more broadly human behaviour. While previous research has largely focused on app usage and keystroke dynamics to predict smartphone use, these analyses are typically limited to making predictions rather than providing explanations or reasoning for observed behaviours. In this exploratory study, we investigate the potential…
Computer Science (10 works) · Psychology (9 works) · Social Psychology (6 works) · Human–computer interaction (4 works) · Applied Psychology (3 works) · Artificial Intelligence (3 works) · Cognitive psychology (3 works) · Data science (3 works) · Impact of Technology on Adolescents (3 works) · Mental Health Research Topics (3 works)