Towards a model for analyzing the cognitive gap in user-product interaction throughout the technological evolution

Abstract

The integration of new technologies into daily life has been radically shifting the nature of the products. Users are surrounded with products, working by technologies and algorithms that they have no information about. This lack of information forms cognitive gap between the user and the product. Exploring efficient ways to integrate technology into daily products with no cognitive gap becomes the main challenge of today's designers. Motivated by this challenge, the study aims to generate a model for analyzing the cognitive gap in user-product interaction in four dimensions: identity, action, intention, and affect. The framework is implemented in the dishwasher product category on a sample set of appliances, representing major milestones in the technological evolution, thereby providing insights into the cognitive gap in technological evolution. As the mechanical structures in the products are being replaced with electronic operating systems one by one, the form of the products changes inevitably, causing irreparable damage to the traditional link between form and function. The weakening link between form and function severely destroys the nature of interaction between user and product, through creating a considerable cognitive gap. As new technologies get integrated in the products, some orthodox interaction elements become obsolete and vanish or gets replaced for thinner, better, smaller versions. This shift induced by developing technologies creates cognitive gap on the distorting, shifting, evolving interaction elements which lost their significant portion of the references regarding functions. The emergence of the cognitive gap is not recent, it has previously studied and defined by many academicians through multiple perspectives like cognitive artifacts, distributed cognition, system image or action flow. So, the study starts by exploring the existing literature through multiple perspectives with the aim of reaching dimensions to analyze and compare the cognitive gap in products. The study aims to develop a cross-genre framework for a model to analyze the cognitive gap at first sight with the aim of providing necessary insights to design products, which can align closely with users' mental models and expectations (less cognitive gap). The study focuses on the cognitive gap at first sight, based on visual input, as pre-use perception of the user is proved to affect the user's perception strongly even after the actual use. Additionally, the surge in online shopping has amplified the impact of visual input in shaping purchasing decisions, increasing the significance of cognitive gap at first sight based on visual input. While the study suggests an evaluation model that can be adapted into various product genres, the field study focuses on a kitchen appliance, the dishwasher. Therefore, the proposed framework is adapted in dishwasher product category, to develop a model for analyzing cognitive gap. The field study investigates the dishwasher samples, which represent significant milestones in technological evolution, to analyze the cognitive gap retrospectively. The dishwasher product category is intentionally selected due to three main reasons: tangibility of kitchen experience, control panel diversity and availability. First, while the kitchen experience primarily revolves with around tangible physical elements, like food, the realm of consumer electronics deals with data. Hence the emergence of cognitive gap, due to miniaturization and dematerialization of the physical elements along with the shift from analog to digital technologies becomes more intriguing to investigate the kitchen industry than the consumer electronics. Second, control panel diversity is aimed to be able to investigate a wide range of cognitive gap. Control panel diversity is reached through the appliance samples, representing milestones of technological evolution. Third, the availability, the dishwasher product category is the only kitchen appliance product category available in the Miele Museum with appliance samples representing the milestones of technological evolution through appliance samples from 30's, 60's, and 70's. The Miele Museum and Miele product portfolio are specifically selected as the main source for appliance samples, as the researcher works at Miele as a design professional and has access to appliance samples and the relevant documentation. The Field Study investigated six appliance samples. Appliance samples M1, M2 and M3 are selected from Miele Museum, while M4, M5 and M6 are selected from current product portfolio. M1 represents the Era 1 which is known with direct tangible feedback, usually forming object symbols and unfamiliar product typology. M2 represents Era 2, which is known with analog, human-focused mechanics, control panels with, and "one control, one function" approach. M3 represents Era 3, which is known with the shift from analogue to digital, smaller but multifunctional elements, and control panels with multiple types of interaction elements. On the other hand, Era 4 is known with high technology acceptance, and loss of identity resulting in rising need for personalization. While M4, M5 and M6 belong to the same era, namely Era 4, they have distinct properties. M4 is full of push buttons in consistent shapes. M5 has a printed back-lit glass touch panel. M6 features the most advanced control panel technology with touch screen. Since the UX discipline deals with all aspects of users' interactions with products, services, and systems, UX evaluation methods naturally become the primary focus for investigating previous studies addressing the cognitive gap. Almost all studies exploring UX evaluation methods start with a literature review to define the impacting dimensions and then develop methods to measure these dimensions. Similarly, the study also starts with an extensive literature review to define the cognitive gap and determine the dimensions of the cognitive gap. Then, Empirical Research is implemented to test and optimized the developed model on dishwasher samples. For the Field Study, mainly the questionnaire method is preferred to collect the data, because of its cost effective, practical and self-reported nature. The dimensions of cognitive gap are defined as identity, action, function, and affect, originally stemming from well accepted UX dimensions such as user value, usability, and affect. Since the cognitive gap is defined as the gap between the user's mental model and the product, the questionnaire set reveals the user's mental model and then compares it with the product itself. For "identity" dimension, the questionnaire set investigates to what extent the appliance can be identified, then compares it with what the appliance sample actually is. For "action" dimension, the questionnaire set investigates to what extent the interaction design element can be manipulated with the planned actions, then compares it with how user is supposed to interact. For "intention" dimension, the questionnaire set investigates to what extent the interaction design element can trigger planned intention, then compares it with what the purpose of this interaction actually is. For "affect" dimension, the questionnaire set investigates to what extent the product can trigger expected or desired emotions, then compares it with how it is supposed to make the user feel. To define the option sets for "identity" dimension, a keyword analysis is conducted on the official Miele webpage. The Miele webpage is chosen as the keyword source, as the logo on the appliance samples offers the main clue for the answer. The keywords collected from the official Miele webpage are grouped, reduced and optimized to reach final option set. To define option sets for "action" and "intention" dimensions, a keyword analysis is conducted on user manuals to collect action keywords. Then the context is analyzed to form a morphologic box, matching action words with interaction elements and intentions (functions). Then, antagonistic actions are grouped and the option set is reduced for optimization, revealing the option set for "action" dimension. The option set for the "intention" dimension is constructed based on the morphological box, generated through the keyword analysis of user manuals. Obsolete functions or one time use functions are ignored. The functions (intentions) with reciprocity or relevance are grouped and the final option set for "intention" dimension is optimized. To generate a rating format and scale for the "affect" dimension, the proposed framework tackles with emotional response. The framework helps to generate a scale to quantify and compare emotional response (affect) to product at first sight (before use). By doing so, it synthesizes the method development processes from Kansei Engineering to ensure adaptability and scale optimization processes from SD Scale methods to ensure the practicality of evaluation and input collection in order to reach more efficient, quantifiable, and adaptable tools. 25 Evaluation adjectives are collected through the Keyword Analysis of appliance buying guides, blogs, and the official Miele website. They are filtered, optimized, and grouped to form adjective antonyms through cluster analysis and binary correlation matrix. Then, the adjective antonyms are crosschecked with existing studies for optimization, then positioned on SD scale to be rated on a 5-point Likert Scale. Through two Pilot studies and follow-up interviews, the adjective pairs are optimized from 15 to seven pairs. The study improves SD Scale methods by replacing the adjective pairs with dimensions, bringing more practicality and more quantifiability. Following the insights from the interviews, the adjective pairs are converted into nouns (Nominalization), increasing the practicality of the rating and quantification process. In its optimized version, the subjects were required to comprehend only one noun to rate instead of 2 adjectives, lightening the language barrier that verbal methods inherently have, and the final scale has seven sub-dimensions, aligning with Miller's Law. In the end, the framework offers analysis of the cognitive gap in multiple dimensions, targeting each dimension separately one by one. The model developed by the proposed framework aims to provide necessary insights for designing products, which can align closely with users' mental models and expectations (less cognitive gap).