Slides from a talk delivered at CHI 2016, San Jose.
Authors: Antti Oulasvirta (Aalto University) and Kasper Hornbaek (University of Copenhagen).
Link to paper: http://users.comnet.aalto.fi/oulasvir/pubs/hci-research-as-problem-solving-chi2016.pdf
Overview: This talk discusses a meta-scientific account of human-computer interaction (HCI) research as problem-solving. We build on the philosophy of Larry Laudan, who develops problem and solution as the foundational concepts of science. We argue that most HCI research is about three main types of problem: empirical, conceptual, and constructive. We elaborate upon Laudan’s concept of problem-solving capacity as a universal criterion for determining the progress of solutions (outcomes): Instead of asking whether research is ‘valid’ or follows the ‘right’ approach, it urges us to ask how its solutions advance our capacity to solve important problems in human use of computers. This offers a rich, generative, and ‘discipline-free’ view of HCI and resolves some existing debates about what HCI is or should be. It may also help unify efforts across nominally disparate traditions in empirical research, theory, design, and engineering.
History and future of Human Computer Interaction (HCI) and Interaction DesignAgnieszka Szóstek
This is the first presentation given for the master course at HITLab, Canterbury University, Christchurch, New Zealand. It shows the snippets of the history of the field of human computer interaction that led to its increasing popularity at the present.
History and future of Human Computer Interaction (HCI) and Interaction DesignAgnieszka Szóstek
This is the first presentation given for the master course at HITLab, Canterbury University, Christchurch, New Zealand. It shows the snippets of the history of the field of human computer interaction that led to its increasing popularity at the present.
Human-Computer Interaction is a discipline concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them” -ACM/IEEE
Presentation - Racial and Gender Bias in AI by Gunay Kazimzade. Gunay Kazimzade is working at the Weizenbaum Institute for the Networked Society and she is also a Ph.D. student in Computer Science at the Technical University of Berlin. After Applied Mathematics and Computer Science degrees, she was involved in the education field and managed two social projects focused on women and children Computer Science education. Trained over 3000 women and children in Azerbaijan. Currently working with the Research Group "Criticality of Artificial Intelligence-based systems". Her main research directions are Gender and racial bias in AI, inclusiveness in AI and AI-enhanced education. She is a TEDx speaker participating and presenting in various conferences and summits happening in Europe.
Human-computer interaction (HCI) is a multidisciplinary field of study focusing on the design of computer technology and, in particular, the interaction between humans (the users) and computers. While initially concerned with computers, HCI has since expanded to cover almost all forms of information technology design
Branch of computer science that develops machines and software with human-like intelligence
top 5 artificial intelligence stocks
artificial intelligence technology
artificial intelligence articles
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artificial intelligence stocks to buy
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Arts-based research
Research using technology
Mixed-methods research
Transformative research frameworks
Indigenous methodologies
This presentation covers arts-based research; the next tech and mixed-methods, the last transformative and Indigenous research.
Interaction Design in Human Computer Interaction by Vrushali Dhanokar. This PPT is useful to every students who study Human Computer Interaction in detail. Specially for TE Students of Information Technology in Pune University. Thank You.
Every researcher is a cyborg! Academic researchers engage various sorts of research in vitro (in the glass) and in vivo (in the living body), or they engage in experimental laboratory work and analyze data in natural in-world experiments. In between, many conduct surveys, focus groups, interviews, and other types of research work. In the computer-assisted qualitative data analysis software (CAQDAS) space, NVivo is one of the foremost tools, enabling the creation of manual codebooks, multimedia analysis, and various forms of “auto” or unsupervised machine learning. NVivo works as a “database” for structured and unstructured data (multimedia). It enables the drawing of content from various social media sites. Technologies augment human analytical capabilities, in the qualitative and quantitative research spaces. This presentation demonstrates some of the capabilities of NVivo. This also addresses how a researcher is changed by the computational capabilities they harness.
Human-Computer Interaction is a discipline concerned with the design, evaluation and implementation of interactive computing systems for human use and with the study of major phenomena surrounding them” -ACM/IEEE
Presentation - Racial and Gender Bias in AI by Gunay Kazimzade. Gunay Kazimzade is working at the Weizenbaum Institute for the Networked Society and she is also a Ph.D. student in Computer Science at the Technical University of Berlin. After Applied Mathematics and Computer Science degrees, she was involved in the education field and managed two social projects focused on women and children Computer Science education. Trained over 3000 women and children in Azerbaijan. Currently working with the Research Group "Criticality of Artificial Intelligence-based systems". Her main research directions are Gender and racial bias in AI, inclusiveness in AI and AI-enhanced education. She is a TEDx speaker participating and presenting in various conferences and summits happening in Europe.
Human-computer interaction (HCI) is a multidisciplinary field of study focusing on the design of computer technology and, in particular, the interaction between humans (the users) and computers. While initially concerned with computers, HCI has since expanded to cover almost all forms of information technology design
Branch of computer science that develops machines and software with human-like intelligence
top 5 artificial intelligence stocks
artificial intelligence technology
artificial intelligence articles
artificial intelligence companies
artificial intelligence stocks to buy
artificial intelligence robots
artificial intelligence in medicine
artificial intelligence wikipedia
Arts-based research
Research using technology
Mixed-methods research
Transformative research frameworks
Indigenous methodologies
This presentation covers arts-based research; the next tech and mixed-methods, the last transformative and Indigenous research.
Interaction Design in Human Computer Interaction by Vrushali Dhanokar. This PPT is useful to every students who study Human Computer Interaction in detail. Specially for TE Students of Information Technology in Pune University. Thank You.
Every researcher is a cyborg! Academic researchers engage various sorts of research in vitro (in the glass) and in vivo (in the living body), or they engage in experimental laboratory work and analyze data in natural in-world experiments. In between, many conduct surveys, focus groups, interviews, and other types of research work. In the computer-assisted qualitative data analysis software (CAQDAS) space, NVivo is one of the foremost tools, enabling the creation of manual codebooks, multimedia analysis, and various forms of “auto” or unsupervised machine learning. NVivo works as a “database” for structured and unstructured data (multimedia). It enables the drawing of content from various social media sites. Technologies augment human analytical capabilities, in the qualitative and quantitative research spaces. This presentation demonstrates some of the capabilities of NVivo. This also addresses how a researcher is changed by the computational capabilities they harness.
1308 226 PMDESIGNING QUALITATIVE RESEARCH PROPOSALSPage.docxmoggdede
1/3/08 2:26 PMDESIGNING QUALITATIVE RESEARCH PROPOSALS
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DESIGNING QUALITATIVE RESEARCH PROPOSALS
Some simple suggestions
Ethnographic or qualitative studies are always to some degree emergent: they're dances in which the
researchers follow the leads of the participants. Still, you've got to have some idea of what kind of dance
event it is (a masked ball or a rave) before you can proceeed. You need, in other words, a clear picture of
the issues and questions you want to investigate, some idea of how you're going to go about investigating
them, but also a readiness to improvise and revise. Ideally, you work out designs with colleagues and
advisors (including participants), but there are also some standard features, forms, and cautions that can be
suggested (the numbered components below are taken from the chapter titles in Joe Maxwell's Qualitative
Research Design: An interactive approach. Thousand Oaks, CA: Sage, 1996, the best available text on
design that I'm aware of (which isn't to say that I agree with all of it). The rest, e.g., my suggestions on
framing research questions, are my own, though it should go without saying that these are simply ways of
thinking that I've absorbed ideas from others over the years.).
1) What's the topic, the focal process you're interested in? What are the goals of the study? Why
do you want to conduct it? Why is it worthwhile?
Qualitative studies are ways of learning about how processes and events unfold. They are usually not useful
for asking questions about the distribution or variance of taken-for-granted-entities. So, a goal for an
ethnographic study might entail examining some taken-for-granted or ignored process that seems important
or central to some vital institution. It might involve questioning familiar categories (asking how they come
to be, for example). And so forth.
2) What is the context for the study? What are the theories, or the research literatures, or the
policy positions you anticipate drawing on, challenging, or addressing, through your research?
Bear in mind that "contexts" are not given in the phenomena or settings you study: in other words, your
research is a wau of creating or defining what counts as a context: you're crafting representations of people,
things, events within certain frames - either ones you've choosen, or the participants have choosen, or ones
promoted by governments, disciplines, organizations (and of course, the processes of contextualization and
framing should be topics of inquiry). My own preference is to recognize layers - or perhaps it would be
better to simply say "alternative" frames - of context. Multiply possible connections. Many theories are
better than one.
3) Research Questions: what do you want to get smart about? What are you presently ignorant
about?
These questions should be how questions, they shoul ...
ABSTRACT
Design has evolved from a craft into an academic discipline, but it
still falls short on defining its own science. I review previous
approaches to Design Science and conclude that the subject–
object dualism is the one of the main obstacles. I then apply the
Metaphysics of Quality to overcome the dualism and propose
Quality as the phenomenon of Design Science. Next, I propose to
utilize the analysis of interaction effects as a mean to investigate
Quality. Last, I recommend steps we can take to mature this new
Design Science and strategies how we can gain the
acknowledgement of the other sciences.
Developing a Socially-Aware Engineering Identity Through Transdisciplinary Le...colin gray
In conjunction with the drive towards human-centered design in engineering education, questions arise regarding how students build and engage a socially-aware engineering identity. In this paper, we describe how students in a transdisciplinary undergraduate program struggle to engage with ontological and epistemological perspectives that draw on that social turn, particularly in relation to human-centered engineering approaches and sociotechnical complexity. We use a critical qualitative meaning reconstruction approach to deeply analyze the meaning-making assumptions of these students to reveal characteristic barriers in engaging with other subjectivities, and related epistemological and ontological claims implicit in these subjectivities. We conclude with implications for encouraging socially-aware identity formation in engineering education.
This document is highly relevant for early learner candidates of doctoral research in different disciplines. The illustrative examples would serve highly instrumental for the potential PhD candidate to visualize a research idea of selective interests and shaping an argument before framing a statement of problem. Additionally, it will also serve useful in learning how to link up purpose of a research, statement of problem, research questions, objectives and working hypotheses.
Observations on typing from 136 million keystrokes - Presentation by Antti Ou...Aalto University
A CHI 2018 presentation by Antti Oulasvirta. "We report on typing behaviour and performance of 168,000 volunteers in an online study. The large dataset allows de- tailed statistical analyses of keystroking patterns, linking them to typing performance. Besides reporting distributions and confirming some earlier findings, we report two new findings. First, letter pairs typed by different hands or fingers are more predictive of typing speed than, for example, letter repetitions. Second, rollover-typing, wherein the next key is pressed before the previous one is released, is surprisingly prevalent. Notwith- standing considerable variation in typing patterns, unsuper- vised clustering using normalised inter-key intervals reveals that most users can be divided into eight groups of typists that differ in performance, accuracy, hand and finger usage, and rollover. The code and dataset are released for scientific use."
Project homepage with the dataset: http://userinterfaces.aalto.fi/136Mkeystrokes/
Neuromechanics of a Button Press: A talk at CHI 2018, April 2018Aalto University
To press a button, a finger must push down and pull up with the right force and timing. How the motor system succeeds in button-pressing, in spite of neural noise and lacking direct access to the mechanism of the button, is poorly understood. This paper investigates a unifying account based on neurome- chanics. Mechanics is used to model muscles controlling the finger that contacts the button. Neurocognitive principles are used to model how the motor system learns appropriate muscle activations over repeated strokes though relying on degraded sensory feedback. Neuromechanical simulations yield a rich set of predictions for kinematics, dynamics, and user performance and may aid in understanding and improving input devices. We present a computational implementation and evaluate predictions for common button types.
"Computational Support for Functionality Selection in Interaction Design" CHI...Aalto University
Talk by Andreas Karrenbauer / Max Planck Institute for Informatics. Presented at the CHI conference (chi2018.acm.org) by Andreas Karrenbauer / Max Planck. In collaboration with Anna Maria Feit, Antti Oulasvita, and Perttu Lähteenlahti
Computational Rationality I - a Lecture at Aalto University by Antti OulasvirtaAalto University
This 2-hour lecture looks at the emerging field of Computational Rationality. Lecture given March 12, 2018, for the Aalto University Master's level course on "Probabilistic Programming and Reinforcement Learning for Cognition and Interaction." Based on: Gershman et al 2015 Science, Lewis et al 2014 Topics in Cog Sci, and Gershman & Daw 2017 Annu Rev Psych
Can Computers Design? Presented at interaction16, March 2, 2016, Helsinki by ...Aalto University
This talk outlines how algorithms may change the way user interfaces are designed. I present foundations and results across a range of user interface types.
Model-Based User Interface Optimization: Part V: DISCUSSION - At SICSA Summer...Aalto University
Tutorial on Model-Based User Interface Optimization. Part V: DISCUSSION. Presented by Antti Oulasvirta (Aalto University) at SICSA Summer School on Computational Interaction 2015. Note: This one-day lecture is divided into multiple parts.
Model-Based User Interface Optimization: Part IV: ADVANCED TOPICS - At SICSA ...Aalto University
Tutorial on Model-Based User Interface Optimization. Part IV: ADVANCED TOPICS.
Presented by Antti Oulasvirta (Aalto University) at SICSA Summer School on Computational Interaction in 2015 in Glasgow. Note: This one-day lecture is divided into multiple parts.
Model-Based User Interface Optimization: Part III: SOLVING REAL PROBLEMS - At...Aalto University
Tutorial on Model-Based User Interface Optimization. Part III: SOLVING REAL PROBLEMS. Presented by Antti Oulasvirta, Aalto University. Presented at SICSA Summer School on Computational Interaction 2015. Note: This one-day lecture is divided into multiple parts.
Model-Based User Interface Optimization: Part II: LETTER ASSIGNMENT - At SICS...Aalto University
Tutorial on Model-Based User Interface Optimization. Part I: LETTER ASSIGNMENT by Anna Feit of Aalto University. Presented at SICSA Summer School on Computational Interaction in 2015 in Glasgow. Note: This one-day lecture is divided into multiple parts.
Model-Based User Interface Optimization: Part I INTRODUCTION - At SICSA Summe...Aalto University
Tutorial on Model-Based User Interface Optimization. Part I: INTRODUCTION.
Presented at SICSA Summer School on Computational Interaction 2015. Note: This one-day lecture is divided into multiple parts.
Improving Two-Thumb Text Entry on Touchscreen DevicesAalto University
Presentation at ACM CHI'13 in Paris by Antti Oulasvirta (Max Planck Institute for Informatics). Work done in collaboration with Keith Vertanen (Montana Tech) and Per Ola Kristensson (University of St Andrews)
Observation of Io’s Resurfacing via Plume Deposition Using Ground-based Adapt...Sérgio Sacani
Since volcanic activity was first discovered on Io from Voyager images in 1979, changes
on Io’s surface have been monitored from both spacecraft and ground-based telescopes.
Here, we present the highest spatial resolution images of Io ever obtained from a groundbased telescope. These images, acquired by the SHARK-VIS instrument on the Large
Binocular Telescope, show evidence of a major resurfacing event on Io’s trailing hemisphere. When compared to the most recent spacecraft images, the SHARK-VIS images
show that a plume deposit from a powerful eruption at Pillan Patera has covered part
of the long-lived Pele plume deposit. Although this type of resurfacing event may be common on Io, few have been detected due to the rarity of spacecraft visits and the previously low spatial resolution available from Earth-based telescopes. The SHARK-VIS instrument ushers in a new era of high resolution imaging of Io’s surface using adaptive
optics at visible wavelengths.
Richard's aventures in two entangled wonderlandsRichard Gill
Since the loophole-free Bell experiments of 2020 and the Nobel prizes in physics of 2022, critics of Bell's work have retreated to the fortress of super-determinism. Now, super-determinism is a derogatory word - it just means "determinism". Palmer, Hance and Hossenfelder argue that quantum mechanics and determinism are not incompatible, using a sophisticated mathematical construction based on a subtle thinning of allowed states and measurements in quantum mechanics, such that what is left appears to make Bell's argument fail, without altering the empirical predictions of quantum mechanics. I think however that it is a smoke screen, and the slogan "lost in math" comes to my mind. I will discuss some other recent disproofs of Bell's theorem using the language of causality based on causal graphs. Causal thinking is also central to law and justice. I will mention surprising connections to my work on serial killer nurse cases, in particular the Dutch case of Lucia de Berk and the current UK case of Lucy Letby.
This pdf is about the Schizophrenia.
For more details visit on YouTube; @SELF-EXPLANATORY;
https://www.youtube.com/channel/UCAiarMZDNhe1A3Rnpr_WkzA/videos
Thanks...!
A brief information about the SCOP protein database used in bioinformatics.
The Structural Classification of Proteins (SCOP) database is a comprehensive and authoritative resource for the structural and evolutionary relationships of proteins. It provides a detailed and curated classification of protein structures, grouping them into families, superfamilies, and folds based on their structural and sequence similarities.
Earliest Galaxies in the JADES Origins Field: Luminosity Function and Cosmic ...Sérgio Sacani
We characterize the earliest galaxy population in the JADES Origins Field (JOF), the deepest
imaging field observed with JWST. We make use of the ancillary Hubble optical images (5 filters
spanning 0.4−0.9µm) and novel JWST images with 14 filters spanning 0.8−5µm, including 7 mediumband filters, and reaching total exposure times of up to 46 hours per filter. We combine all our data
at > 2.3µm to construct an ultradeep image, reaching as deep as ≈ 31.4 AB mag in the stack and
30.3-31.0 AB mag (5σ, r = 0.1” circular aperture) in individual filters. We measure photometric
redshifts and use robust selection criteria to identify a sample of eight galaxy candidates at redshifts
z = 11.5 − 15. These objects show compact half-light radii of R1/2 ∼ 50 − 200pc, stellar masses of
M⋆ ∼ 107−108M⊙, and star-formation rates of SFR ∼ 0.1−1 M⊙ yr−1
. Our search finds no candidates
at 15 < z < 20, placing upper limits at these redshifts. We develop a forward modeling approach to
infer the properties of the evolving luminosity function without binning in redshift or luminosity that
marginalizes over the photometric redshift uncertainty of our candidate galaxies and incorporates the
impact of non-detections. We find a z = 12 luminosity function in good agreement with prior results,
and that the luminosity function normalization and UV luminosity density decline by a factor of ∼ 2.5
from z = 12 to z = 14. We discuss the possible implications of our results in the context of theoretical
models for evolution of the dark matter halo mass function.
Introduction:
RNA interference (RNAi) or Post-Transcriptional Gene Silencing (PTGS) is an important biological process for modulating eukaryotic gene expression.
It is highly conserved process of posttranscriptional gene silencing by which double stranded RNA (dsRNA) causes sequence-specific degradation of mRNA sequences.
dsRNA-induced gene silencing (RNAi) is reported in a wide range of eukaryotes ranging from worms, insects, mammals and plants.
This process mediates resistance to both endogenous parasitic and exogenous pathogenic nucleic acids, and regulates the expression of protein-coding genes.
What are small ncRNAs?
micro RNA (miRNA)
short interfering RNA (siRNA)
Properties of small non-coding RNA:
Involved in silencing mRNA transcripts.
Called “small” because they are usually only about 21-24 nucleotides long.
Synthesized by first cutting up longer precursor sequences (like the 61nt one that Lee discovered).
Silence an mRNA by base pairing with some sequence on the mRNA.
Discovery of siRNA?
The first small RNA:
In 1993 Rosalind Lee (Victor Ambros lab) was studying a non- coding gene in C. elegans, lin-4, that was involved in silencing of another gene, lin-14, at the appropriate time in the
development of the worm C. elegans.
Two small transcripts of lin-4 (22nt and 61nt) were found to be complementary to a sequence in the 3' UTR of lin-14.
Because lin-4 encoded no protein, she deduced that it must be these transcripts that are causing the silencing by RNA-RNA interactions.
Types of RNAi ( non coding RNA)
MiRNA
Length (23-25 nt)
Trans acting
Binds with target MRNA in mismatch
Translation inhibition
Si RNA
Length 21 nt.
Cis acting
Bind with target Mrna in perfect complementary sequence
Piwi-RNA
Length ; 25 to 36 nt.
Expressed in Germ Cells
Regulates trnasposomes activity
MECHANISM OF RNAI:
First the double-stranded RNA teams up with a protein complex named Dicer, which cuts the long RNA into short pieces.
Then another protein complex called RISC (RNA-induced silencing complex) discards one of the two RNA strands.
The RISC-docked, single-stranded RNA then pairs with the homologous mRNA and destroys it.
THE RISC COMPLEX:
RISC is large(>500kD) RNA multi- protein Binding complex which triggers MRNA degradation in response to MRNA
Unwinding of double stranded Si RNA by ATP independent Helicase
Active component of RISC is Ago proteins( ENDONUCLEASE) which cleave target MRNA.
DICER: endonuclease (RNase Family III)
Argonaute: Central Component of the RNA-Induced Silencing Complex (RISC)
One strand of the dsRNA produced by Dicer is retained in the RISC complex in association with Argonaute
ARGONAUTE PROTEIN :
1.PAZ(PIWI/Argonaute/ Zwille)- Recognition of target MRNA
2.PIWI (p-element induced wimpy Testis)- breaks Phosphodiester bond of mRNA.)RNAse H activity.
MiRNA:
The Double-stranded RNAs are naturally produced in eukaryotic cells during development, and they have a key role in regulating gene expression .
Professional air quality monitoring systems provide immediate, on-site data for analysis, compliance, and decision-making.
Monitor common gases, weather parameters, particulates.
THE IMPORTANCE OF MARTIAN ATMOSPHERE SAMPLE RETURN.Sérgio Sacani
The return of a sample of near-surface atmosphere from Mars would facilitate answers to several first-order science questions surrounding the formation and evolution of the planet. One of the important aspects of terrestrial planet formation in general is the role that primary atmospheres played in influencing the chemistry and structure of the planets and their antecedents. Studies of the martian atmosphere can be used to investigate the role of a primary atmosphere in its history. Atmosphere samples would also inform our understanding of the near-surface chemistry of the planet, and ultimately the prospects for life. High-precision isotopic analyses of constituent gases are needed to address these questions, requiring that the analyses are made on returned samples rather than in situ.
3. SHAPE OUR CAREERS
AND OUR FIELD
BELIEF SYSTEMS
Not well-
articulated Not internally
consistent Not value-free
4. “Novelty is important in HCI research”
“A good paper reports
implications to practitioners”
“HCI should be more scientific”
“Cognitive modeling is passe”
5. “What should I research?”
“What is good HCI?”
“Is this paper good?”
“Is HCI progressing?”
mportant in HCI research”
orts
titioners”
re scientific”
modeling is passe”
Thinking
8. A UNIFYING CONCEPT
PROBLEM-SOLVING CAPACITY
“Instead of asking whether research is
‘valid’ or follows the ‘right’ approach, it
urges us to ask how its solutions advance
our capacity to solve important problems
in human use of computers.“
9. MORE THAN JUST A LENS
’95% OF HCI RESEARCH’
Our identity
as a field
Inclusive
without
being naive
Generate
new ideas,
steer
thinking
10. EXISTING ACCOUNTS CONSTRAIN RESEARCH
‘Hard science’
‘In the wild’
‘Inter-discipline’
‘Waves’
‘Epochs’
‘Novelty’
‘Benefit’
‘Design implications’
Problem OutcomeApproach
11. A NEW UNIT OF ANALYSIS
Problem
OutcomeSolution
12. LARRY LAUDAN
In appraising the merits of theories, it is
more important to ask whether they
constitute adequate solutions to
significant problems than it is to ask
whether they are ‘true’, ‘corroborated’,
‘well-confirmed’ or otherwise justifiable
within the framework of contemporary
epistemology.
‘Progress and its Problems’ 1978
13. ‘RESEARCH PROBLEM’
“…not what we mean by the term in
ordinary language. It is defined via
inabilities and absences occurring
in descriptions; knowledge; or, as
often in HCI, constructive solutions.”
design problem
14. JUST THREE PROBLEM TYPES
“One can now see similarities and
differences between, say, an
observational study of a novel
technology and a rigorous
laboratory experiment, without
being bound by their traditions.”
COLLAPSING MULTI-DISCIPLINARITY
15. THREE PROBLEM TYPES IN HCI
Research problems in HCI
Empirical
Unknown phenomena
Unknown factors
Unknown effects
Conceptual
Implausibility
Inconsistency
Incompatibility
Constructive
No known solution
Partial solution
Inability to deploy/implement
OVERVIEW
16. PROBLEM-SOLVING CAPACITY
Significance
Addresses a
problem important
to our stakeholders
Effectiveness
Solves essential
aspects of it
Transfer
and transfers to
other problem-
instances.
Efficiency
…and with little
use of resources
… with high
reliability & validity
Confidence
DEFINITION
17. Tangible Bits
Ishii & Ulmer, 1997
Constructive
Conceptual
TWO CLASSIC HCI CONTRIBUTIONS
Fitts’ Law
ILLUSTRATIVE EXAMPLE
18. EXAMPLES OF CONSTRUCTIVE CONTRIBUTIONS
Problem:
Significance
Solution:
Capacity
Tangible Bits
All input
Pointing tasks
Vision, demonstrators
Model
Fitts’ Law
19. HCI RESEARCH AS PROBLEM-
SOLVING
ZOOMING OUT
Achieved
progress
Research
problems Desired
problem-solving
capacities
Description
of a field
20. In a paper,
often more
than one
type present
All problem
types and
capacities
present High
tolerance
for risk
‘Significance’
often shaped by
society/industry
Achieved
progress
Research
problems Desired
problem-solving
capacities
SOLVING
HCI in
general
21. In a paper,
often more
than one
type present
All problem
types and
capacities
present High
tolerance
for risk
‘Significance’
often shaped by
society/industry
Capacities
often
ambiguous
CHI’15
Best PapersMostly
empirical and
constructive
Achieved
progress
capacities
Problems
well-
described
We miss conceptual work
relating empirical and
constructive capacities
22. EXPLAINING ‘THE BIG HOLE IN HCI’
Problem-solving
capacity
Time
Paradigm-shifting
‘Leapfrogging’
23. IN OUR BELIEF SYSTEMS
“Novelty is important”
“HCI is about design”
“HCI should be scientific”
EXPOSING FLAWS
Ignores the types of
problems and capacities we
need in HCI.
Ignores either solution or
problem.
25. A DISCIPLINE-FREE
VIEW OF HCI RESEARCH
SUMMARY
Embraces variety without naivety
Shows that we need work on conceptual problems
Shows that we do have significant progress
You can use this to generate and refine research ideas
A single concept; much richer than “solutionism”
26. HCI Research as Problem-Solving / CHI’16
COMMON OBJECTIONS
1. It’s solutionism
2. It does not establish the boundaries of HCI with other disciplines
3. It ignores the role of art in HCI
4. It ignores the role of curiosity
5. Some topics are too subjective to be problem-solving
6. HCI, especially in design, is inherently messy
7. The view is iffy and leads to lot of handwaving
8. It ignores HCI’s impact on society
SCOPE AND LIMITATIONS
27. We thank Susanne Bødker, Stuart Reeves, Barry Brown,
Antti Salovaara, Giulio Jacucci, Vassilis Kostakos, Pierre
Dragicevic, Andrew Howes, and Pertti Saariluoma.
Instead of asking whether research is ‘valid’ or
follows the ‘right’ approach, it urges us to ask how
its solutions advance our capacity to solve
important problems in human use of computers.
HCI RESEARCH AS
PROBLEM-SOLVING