Machine Learning is a technology that has risen in popularity in the last decade. Designers face difficulties in working with Machine Learning as a design material. In order to help designers to cope with this material, many different approaches have been suggested, from books to insights of experienced designers with Machine Learning. In this research, the focus is on the users’ perceptions on Machine Learning and how these could contribute to better design. For this purpose, 10 participants deployed probes to investigate the term Machine Learning. Probes consisted of simple tasks that provoked participants to recognize Machine Learning elements in applications they already use and were deployed with the use of their smart phones. Participants formed personalized perceptions on Machine Learning which varied from creativity in Machine Learning to preoccupations about data use. Based on these findings, suggestions to designers were proposed. Moreover, a secondary research question that emerged was the difficulties the researcher faced while working with probing on Machine Learning user experiences for the specific research. / Maskininlärning är ett teknologi som har blivit populär det senaste decenniet. Som designer kan det vara svårt att jobba med maskininlärning som ett “designmaterial". Olika tillvägagångssätt har föreslagits för att hjälpa designers att hantera det här material. I studien som presenteras här läggs fokus på användarens uppfattningar om maskininlärning och hur deras förståelse skulle kunna bidra till bättre design. Tio deltagare använde så kallade “probes" i syfte att undersöka hur vi möter maskininlärning i vardagen. Dessa “probes" bestod av enkla uppgifter som uppmuntrade deltagare att notera och utforska hur maskininlärning ingår som element i tillämpningar som de använder i t ex smartphones. Deltagarna uttryckte sin personliga förståelse och funderingar om maskininlärning, vilket omfattade allt från kreativitet till oro kring hur personliga data används i dessa system. Baserat på en analys av resultaten formulerar vi råd till hur en designer ska utforma interaktion med maskininlärningssystem. Slutligen adderar vi en reflektion om svårigheterna med att använda probes för att studera maskininlärning.

This thesis presents the design and implementation of an application for a large interactive public display. The role of the application is to visualize and control the sensor systems that are located in the Human Health and Activity Laboratory, a smart home research facility at Luleå University of Technology. These sensor systems work independently from each other and present different kinds of data while there is no easy way to find out if the systems are active or if there are any problems. There is also a need to be able to present the laboratory, displaying images for public users with descriptions. The project had two main phases, where the first one was to choose frameworks and database while also plan a user interface for the application that was useful for people using the laboratory. This was done by first drawing the application on paper to define functionality and appearance and then in Power Point where two people got to test the application and use their feedback as a result for the implementation. The second phase was to implement the application and integrate the systems, which included figuring out how to do this in the best possible way and lessons learned from it. It also included figuring out how to create a real dynamic menu depending on URL location and rewriting and rethinking a lot of CSS styling to create the design that was wanted. As a conclusion, the project was a success and it is a very good and easily extendable solution for the problem stated and it has a potential to be a very useful tool in the future.

No description available.

This qualitative study investigated the extent to which a diverse sub-set of e-learning designers were aware of UX principles and practices, where their e-learning design practices overlapped with established UX practices, and where UX principles might benefit e-learning designers. E-learning has grown dramatically as an area of focus in instructional design within the last decade and a half. This growth suggests a need for a better understanding of design tools, concepts and principles that can guide an e-learning designer to design better and more effective instruction. One field of design that has potentially had an impact on e-learning design recently is user experience (UX) design. Both fields of UX and e-learning are concerned with designing interactions with technology, but while there are some shared ideas and terms between the two, there has been no research into the perceptions and understanding of UX tools by practicing instructional designers. Nine professional e-learning designers were interviewed to understand their perspective and experience.The findings of this study resulted in four themes and several subthemes. In general the participants of the study were not familiar with the formal practices of UX design. Many were also not familiar with several of the seminal works of the UX design field. The emergent themes suggest there are similar concerns between UX design and e-learning design. There were varying perceptions of the role of an e-learning designer as well as a broad spectrum of perception of what qualifies as good e-learning design. Participants reported the e-learning design field has numerous practitioners who lack formal training in instructional design principles in addition to limited training in other design disciplines. Participants also discussed constraints that could impact their ability to embrace UX practices. Findings suggest e-learning design practitioners and students of the field would likely benefit from a greater awareness of, or even formal training in UX practices. Additional research into the shared practices of UX and e-learning design could also likely open new opportunities to advance the practice of e-learning design.

Usability and User Experience are two important factors that play a big role in user interaction and design. A poorly designed website can drive users away in frustration, costing a company money. A well-designed website will create a positive user experience, which will help attract new customers. These users will remain the company's customers. The study is looking into whether there is a difference in usability and user experience between two types of webpages. One uses different design principles while the other does not apply to any design principles. This study uses six methods of data collection to investigate the usability and user experience of the astrastad.se website and even find out what actions should be taken to help the company with a usability deficiency. These methods have been implemented to address user problems with using the website. In the study, it was found that there are a great variety of results between the tests.

This thesis aims to explore how we can empower users through using recommendation systems. Recommendation systems are all around us on the web, however today’s implementation is not necessarily that interactive. Literature argues for interaction designers to learn and get involved in the design of recommender systems and processes where AI technology is implemented. Moreover, designing with Artificial Intelligence as a material is explored and what interaction designers need to keep in mind when designing with it. The design process sets out to explore new ways of interacting with recommendation systems on the web. The process has used various design activities which generated several design proposals. These design proposals have been put through user testing using anonymous participants, in order to find a final design solution. The main conclusions are that informing and including users how the system works are important factors if we want users to interact with the recommender systems. It is not necessarily the most interactive design proposal that is the best solution, but rather one that is likely to interact with.

The less glamorous aspects of a transportation system'­s infrastructure, such as signage, ticketing systems, and wayfinding elements, typically get little or no attention from creative professionals. Instead they are purchased directly from manufacturers as minimally customized off-the-shelf components. Paradoxically, these parts that go unconsidered and undesigned are what transit riders most directly interact with, and what most affects their experience of the transit system/product. This thesis focuses specifically on the Washington DC Metro Area Transportation Authority's (WMATA) Metrorail, aiming to reshape the entrance segment of this public transportation experience by increasing both appeal and accessibility. The design process began with primary and secondary design research, using observational and interactive methods to produce an informed picture of Metrorail users'­ current perspectives. A design strategy was then developed from the collective research findings, which led to a period of blue-sky ideation and finally the design of elegant and accessible mass transit entrance system components. / Master of Science

No description available.

No description available.

This dissertation, Making Sense of Digital Content Moderation from the Margins, examines how content creators who are marginalized by race, sexuality, gender, ethnicity, and disability understand their experiences of content moderation on the social media platform TikTok. Using critical interface and narrative-based inquiry methods with six marginalized content creators on TikTok, I argue that marginalized creators navigate the opaque content moderation infrastructure of TikTok by drawing on their embodied experiences. The key research questions ask how these content creators interpret TikTok's platform policies and processes through their interactions on the app and how these interpretations influence content creation on TikTok and how creators feel about moderation in the absence of platform transparency about how content is moderated. To answer these questions, I conducted narrative-driven interviews with six TikTok creators and analyzed these stories alongside online testimonials in eight Change.org petitions. My analysis revealed that lack of transparency around TikTok's algorithmic curation and moderation contributes to content creators feeling alienated, exploited, frustrated, and unwelcome on the platform and influences content creators to adapt their content to avoid moderation, oftentimes by self-censoring themselves and aspects of their marginalized identities. Over time, the accumulation of content moderation micro-interactions diminishes the ability of marginalized content creators to trust content moderation processes. My analysis also shows how TikTok's user experience design and opaque content moderation practices contribute to an affective platform environment in which creators are compelled to speak out and across creator networks about such gaps in experience and platform policy. I conclude with a discussion of how my findings about content moderation and transparency contribute to conversations in writing-related scholarship, especially as it pertains to writing assessment, technical communication, and algorithmic research methodologies. / Doctor of Philosophy / In recent years, marginalized content creators on TikTok have sounded the alarm about the way that the platform's content moderation and algorithmic recommendation disadvantages marginalized creators. This dissertation, Making Sense of Digital Content Moderation from the Margins, examines how content creators who are marginalized by race, sexuality, gender, ethnicity, and disability understand their experiences of content moderation on the social media platform TikTok. The key research questions ask how these content creators interpret TikTok's platform policies and processes through their interactions on the app and how these interpretations influence content creation on TikTok and how creators feel about moderation in the absence of platform transparency about how content is moderated. To answer these questions, I conducted narrative-driven interviews with six TikTok creators and analyzed these stories alongside online testimonials. My analysis revealed that lack of transparency around TikTok's algorithmic curation and moderation contributes to content creators feeling alienated, exploited, and unwelcome on the platform and influences content creators to adapt their content to avoid moderation, oftentimes by self-censoring themselves and aspects of their marginalized identities. Moreover, I found that TikTok isolates user experiences of biased content moderation which compels creators to speak out and across creator networks about discriminatory experiences of platform policy.