Multimodal language learning environment of the Korean digital kitchen : a study on the impact of physicality and technological affordances on Korean vocabulary learning

PhD ThesisTask Based Language Learning and Teaching (TBLT) has been integrated with computer-assisted language learning (CALL), contributing to pedagogical developments in the field of foreign/second language teaching and learning (Thomas and Reinders, 2010). While the majority of studies have used the integrated pedagogy inside the classroom context, little attention has been paid to the area outside the classroom (Seedhouse et al., 2013; Seedhouse et al., 2014; Preston et al., 2015). This issue has recently been addressed by the European Digital Kitchen (EDK) project team (Seedhouse, 2017), which has successfully investigated the efficacy of digital technology on foreign language learning out of the classroom. However, as the EDK was designed as a holistic learning environment in which many different environmental factors would contribute to learning, there was a need to disaggregate some of these factors and discover which factors were more or less significant. In order to determine one of the environmental factors to learning, this study attempted to use the technological components of a previous project to create Korean pedagogical materials. This formed the Korean Digital Kitchen (KDK), a real-world environment of a kitchen where students can simultaneously learn Korean language and culture by carrying out the real-world task of cooking. Korean is one of the important global languages to be taught, according to an Ethnologue report (Lewis et al., 2016). Based on the literature on vocabulary learning, especially Nattinger’s (1988) claim that touching and manipulating real objects, as opposed to seeing them, increases learnability, this study explored whether kinesthetic mode adds extra value to foreign language learning processes. Would there be any significant difference between vocabulary learning which involves seeing the learning items only in a classroom and learning which also involves touching the items in the KDK? Thus, this study examined the power of physicality. Furthermore, the salience of real-world and pedagogical tasks has been investigated as factors to different level of vocabulary learning. To this end, a quasi-experimental design was employed for users to conduct two cooking sessions, one in a digital kitchen by using real objects and the other in a classroom by looking at pictures/photos in the textbook. Participants were 48 adults of both British and international origins, living in Newcastle, UK, coming from 20 different countries. To determine which environment between a digital kitchen and a classroom is more conducive to vocabulary learning, users needed to carry out two ii different recipes in the two locations in order to control a practice effect. Subjects went through the real-life cooking activities in three stages of TBLT in both settings using two different recipes with two different set of vocabularies. There were tests before and after cooking to compare their scores to examine the results of learning. Ten vocabulary noun items were targeted in this research. In addition to test score data, three more data sources were employed, namely questionnaires, semi-structured interviews and video-observations for triangulation, revealing the outcomes and processes of learning in two different learning environments. A series of data sets clearly demonstrated which of the two learning settings was more effective to learn foreign language vocabulary and culture in and what their attitudes towards a digitalized learning environment were. Findings suggest that physicality in the KDK makes students link the word and cultural aspects to their memory better than simply looking at photos of objects in the classroom. The learning differences reached statistical significance. Other environmental factors such as technology and its affordances may have contributed to different learning outcomes, playing a role in learners taking positive attitudes (Stricker et al., 2004). In contrast, users in the conventional setting demonstrated relatively less learning, due to fewer senses and its typical features such as the relationship with a teacher, less interaction with peers (Shen et al., 2008) and boredom. It is these differences that contributed to the different results and processes of learning in two settings. From these findings, it could be concluded that the digital kitchen can provide a motivating learning environment which is multi-modal, multi-sensory, multi-interactional, multi-experiential and multi-layered. It is physicality, meaningful tasks and computer technology that foster learning in vocabulary and cultural aspects. This project contributes to building up one more dimension of psycholinguistic factor in language learning, and supports the development of innovative ICT for foreign language learning across the world

Jamie Oliver as a Promoter of a Lifestyle: Recontextualisation of a Culinary Discourse and the Transformation of Cookbooks in Slovenia.

This thesis examines the recontextualization and localization of global culinary discourse to Slovenia after its independence from Yugoslavia in 1991 and its transition into a free market economy. Slovenia and its emerging celebrity chefs, Luka and Valentina Novak, are an example of the 'local', whereas the global is represented by the British celebrity chef Jamie Oliver. The study is based on culinary texts from Oliver and the Novaks' cookbooks. However, 'standard' Slovene cookbook texts are also analysed with the aim of showing the difference between the previous educational role of cookbooks and the contemporary, increasingly edutaining role of the new 'celebrity' cookbooks. This study is situated within critical discourse analysis and it generally draws on the methodological framework of the discourse-historical approach ('DHA') (Reisigl and Wodak 2001), but also combines this with theoretical insights from the dialectic-relational approach (Fairclough 2010, 1992, 2001 [1989]). Its underlying theoretical focus has been recontextualization, which is one of the salient concepts within 'CDA' (e. g. Wodak and Fairclough 2010; Chouliaraki 1998). The model of recontextualization that I presented in this thesis (based on the definition of discourse in 'DHA') enables me to show how global culinary discourse has been recontextualised from Britain to Slovenia, via, firstly, a translation of Jamie Oliver's cookbooks, and secondly, via the production of an original local discourse. The main claim of this thesis is that under the influence of global culinary discourse, local representations related to food and taste change, and so do cookbooks as genres. While recontextualization as translation results in appropriation of the text to the local circumstances in terms of genre conventions, branding opportunities, country-related representations (e. g. Italy) and the reconfirmation of the national identity, the second phase of recontextualisation reveals the characteristics of the locally produced discourse based on global characteristics. Compared to the 'standard' Slovene cookbooks, its 'celebrity' variant aims to reconstructs the national culinary identity via legitimation of the tastes of the new middle classes. Influenced by the global model, the Novaks' tend to represent food and foodstuffs relying on characteristics found in advertising while social actors are often synthetically personified (Fairclough 1989). Likewise, various perspectives construct a seemingly democratisized discourse and disperse the top-down authority as found in 'standard' cookbooks

Food - Media - Senses: Interdisciplinary Approaches

Food is more than just nutrition. Its preparation, presentation and consumption is a multifold communicative practice which includes the meal's design and its whole field of experience. How is food represented in cookbooks, product packaging or in paintings? How is dining semantically charged? How is the sensuality of eating treated in different cultural contexts? In order to acknowledge the material and media-related aspects of eating as a cultural praxis, experts from media studies, art history, literary studies, philosophy, experimental psychology, anthropology, food studies, cultural studies and design studies share their specific approaches

Interactive recipe instructions: supporting cooks with better designs

In the last decade in HCI there has been a growing interest in using interactive technology to support human-food activities such as meal planning, shopping and cooking. However, despite the principles of UCD, few researchers have made use of empirical research of users’ human-food activities to ground their system designs, few evaluated their systems with users against a control and most have designed systems with the needs of younger people in mind. In the first two studies I investigated the food related activities of older adults using focus groups and a food and shopping diary with post diary interview. I found that older adults’ food related activities were both routinized and flexible. They were knowledgeable about food, how to plan meals, shop and prepare food and did not have need for technological support. The design assumptions of early food-related systems do not generalise to older adults. In the second two studies I investigated how cooks interact with recipe instructions in order to inform the design of interactive recipe systems. In the first cooking study I investigated the effect (1) of shorter recipe steps and (2) of integrating the instructions and information normally located in the ingredient list into the text of recipe steps. I found that cooks do not read or perform the tasks of recipe instructions in sequence. In part this is because of the nature of recipe procedures and in part because they read ahead to understand the narrative of ingredients to help them interpret the current step. Cooks found instructions with ingredient information integrated clearer and easier to read because integrating the information reduces the need for the cook to look up and mentally integrate information from different sources. In the second cooking study I investigated the effects (1) of adding pictures to recipe steps and (2) of presenting an overview of the structure of the recipe procedure. I found that cooks liked pictures with the recipe steps but they did not reduce problems or errors. Cooks preferred recipes with a structural overview because it enabled them to understand the process and to plan and perform tasks in parallel. Results suggest that the overview presentation, by highlighting the sub-goals of recipe instructions, reduced problems due to recipe content experienced by cooks. The implications for design show that future interactive recipe systems should integrate ingredient information into the recipe steps, support cooks to move around the recipe steps non- sequentially, support cooks to perform more than one step in parallel and provide an overview of the procedure with sub-goals

Alaska sourdough: bread, beards and yeast

Thesis (M.A.) University of Alaska Fairbanks, 2017Sourdough is a fermented mixture of flour and water used around the world to leaven dough. In this doughy world wide web of sourdough, one thread leads to Alaska and the Yukon Territory. Commonly associated with the gold rush era, sourdough is known both as a pioneer food and as a title for a long-time resident. Less well known is the live culture of microbes, yeasts and bacteria that were responsible for creating the ferment for nutritious bread, pancakes, and biscuits on the trail. Through the lens of sourdough, this study investigates the intersection of microbes and human culture: how microbes contribute taste and texture to baked goods; why sourdough, made from imported ingredients, became a traditional food in the North; and how "Sourdough" grew to signify an experienced northerner. A review of research about sourdough microflora, coupled with excerpts from archival sources, illuminates how human and microbial cultures intertwined to make sourdough an everyday food in isolated communities and mining camps. Mastery of sourdough starter in primitive kitchens with fluctuating temperatures became a mark of accomplishment. Meanwhile, as transient fortune seekers ushered in the gold rush era, experienced Sourdoughs continued to take pride in a common identity based on shared experiences unique to northern living.Introduction -- Chapter 1. Microhistory and microbes -- 1.1. Microhistory -- 1.2. Sourdough microbiology -- 1.2.1. A harvest out of thin air -- 1.2.2. Microbial solidarity in sourdough starter -- 1.2.2.1. Synergy in sugars: carbohydrate non-competition -- 1.2.2.2. Monosaccharides and disaccharides -- 1.2.2.3. Acidic growth requirements -- 1.2.2.4. Antimicrobial byproducts of fermentation -- 1.2.3. Microbial variation and taste -- 1.2.4. Homegrown microbes -- 1.2.5. Location and ingredients -- 1.2.6. Airborne and "flour" borne ingredients -- 1.2.7. Starters through time -- 1.2.8. Sourdough variations -- 1.2.9. Temperature -- Chapter 2: Leavens through time -- 2.1. Sourdough origins -- 2.2. Barm and brewer's yeast in Europe and North America -- 2.2.1. Hop rising -- 2.3. Baker's yeast -- 2.4. Chemical leavens: baking soda and baking powder -- Chapter 3. Sourdough flourishes on the frontier -- 3.1. Sourdough bread and biscuits in the West -- 3.2. Sourdough in the Klondike -- 3.2.1. Sourdough skills -- 3.2.2. Challenges and vicissitudes of camp cooking -- 3.3. Culinary legacy of the Gold Rush -- Chapter 4: The Sourdough moniker -- 4.1. The Trail of sourdough in the West 1867-1897 -- 4.1.1. Sourdough in Eastern newspapers -- 4.2. Sourdough in Western news -- 4.2.1. Sourdough place names -- 4.2.2. Sourdough nicknames -- 4.2.3. Sourdough metaphor -- 4.2.4. Veterans of the West -- 4.3. Sourdough, Cheechako and the Klondike Gold Rush -- 4.3.1. Sourdough in the press 1897-1899 -- 4.3.2. Sourdoughs in the news -- 4.3.3. Time, skill and tenacity -- 4.3.4. Who could become a sourdough -- 4.4 Post-Klondike sourdoughs -- 4.5 Sourdough legacies -- 4.5.1. The sourdough legacy in the West -- 4.5.2. The sourdough legacy in the North -- Conclusion -- Bibliography -- Appendix

Workload-aware systems and interfaces for cognitive augmentation

In today's society, our cognition is constantly influenced by information intake, attention switching, and task interruptions. This increases the difficulty of a given task, adding to the existing workload and leading to compromised cognitive performances. The human body expresses the use of cognitive resources through physiological responses when confronted with a plethora of cognitive workload. This temporarily mobilizes additional resources to deal with the workload at the cost of accelerated mental exhaustion. We predict that recent developments in physiological sensing will increasingly create user interfaces that are aware of the user’s cognitive capacities, hence able to intervene when high or low states of cognitive workload are detected. In this thesis, we initially focus on determining opportune moments for cognitive assistance. Subsequently, we investigate suitable feedback modalities in a user-centric design process which are desirable for cognitive assistance. We present design requirements for how cognitive augmentation can be achieved using interfaces that sense cognitive workload. We then investigate different physiological sensing modalities to enable suitable real-time assessments of cognitive workload. We provide empirical evidence that the human brain is sensitive to fluctuations in cognitive resting states, hence making cognitive effort measurable. Firstly, we show that electroencephalography is a reliable modality to assess the mental workload generated during the user interface operation. Secondly, we use eye tracking to evaluate changes in eye movements and pupil dilation to quantify different workload states. The combination of machine learning and physiological sensing resulted in suitable real-time assessments of cognitive workload. The use of physiological sensing enables us to derive when cognitive augmentation is suitable. Based on our inquiries, we present applications that regulate cognitive workload in home and work settings. We deployed an assistive system in a field study to investigate the validity of our derived design requirements. Finding that workload is mitigated, we investigated how cognitive workload can be visualized to the user. We present an implementation of a biofeedback visualization that helps to improve the understanding of brain activity. A final study shows how cognitive workload measurements can be used to predict the efficiency of information intake through reading interfaces. Here, we conclude with use cases and applications which benefit from cognitive augmentation. This thesis investigates how assistive systems can be designed to implicitly sense and utilize cognitive workload for input and output. To do so, we measure cognitive workload in real-time by collecting behavioral and physiological data from users and analyze this data to support users through assistive systems that adapt their interface according to the currently measured workload. Our overall goal is to extend new and existing context-aware applications by the factor cognitive workload. We envision Workload-Aware Systems and Workload-Aware Interfaces as an extension in the context-aware paradigm. To this end, we conducted eight research inquiries during this thesis to investigate how to design and create workload-aware systems. Finally, we present our vision of future workload-aware systems and workload-aware interfaces. Due to the scarce availability of open physiological data sets, reference implementations, and methods, previous context-aware systems were limited in their ability to utilize cognitive workload for user interaction. Together with the collected data sets, we expect this thesis to pave the way for methodical and technical tools that integrate workload-awareness as a factor for context-aware systems.Tagtäglich werden unsere kognitiven Fähigkeiten durch die Verarbeitung von unzähligen Informationen in Anspruch genommen. Dies kann die Schwierigkeit einer Aufgabe durch mehr oder weniger Arbeitslast beeinflussen. Der menschliche Körper drückt die Nutzung kognitiver Ressourcen durch physiologische Reaktionen aus, wenn dieser mit kognitiver Arbeitsbelastung konfrontiert oder überfordert wird. Dadurch werden weitere Ressourcen mobilisiert, um die Arbeitsbelastung vorübergehend zu bewältigen. Wir prognostizieren, dass die derzeitige Entwicklung physiologischer Messverfahren kognitive Leistungsmessungen stets möglich machen wird, um die kognitive Arbeitslast des Nutzers jederzeit zu messen. Diese sind in der Lage, einzugreifen wenn eine zu hohe oder zu niedrige kognitive Belastung erkannt wird. Wir konzentrieren uns zunächst auf die Erkennung passender Momente für kognitive Unterstützung welche sich der gegenwärtigen kognitiven Arbeitslast bewusst sind. Anschließend untersuchen wir in einem nutzerzentrierten Designprozess geeignete Feedbackmechanismen, die zur kognitiven Assistenz beitragen. Wir präsentieren Designanforderungen, welche zeigen wie Schnittstellen eine kognitive Augmentierung durch die Messung kognitiver Arbeitslast erreichen können. Anschließend untersuchen wir verschiedene physiologische Messmodalitäten, welche Bewertungen der kognitiven Arbeitsbelastung in Realzeit ermöglichen. Zunächst validieren wir empirisch, dass das menschliche Gehirn auf kognitive Arbeitslast reagiert. Es zeigt sich, dass die Ableitung der kognitiven Arbeitsbelastung über Elektroenzephalographie eine geeignete Methode ist, um den kognitiven Anspruch neuartiger Assistenzsysteme zu evaluieren. Anschließend verwenden wir Eye-Tracking, um Veränderungen in den Augenbewegungen und dem Durchmesser der Pupille unter verschiedenen Intensitäten kognitiver Arbeitslast zu bewerten. Das Anwenden von maschinellem Lernen führt zu zuverlässigen Echtzeit-Bewertungen kognitiver Arbeitsbelastung. Auf der Grundlage der bisherigen Forschungsarbeiten stellen wir Anwendungen vor, welche die Kognition im häuslichen und beruflichen Umfeld unterstützen. Die physiologischen Messungen stellen fest, wann eine kognitive Augmentierung sich als günstig erweist. In einer Feldstudie setzen wir ein Assistenzsystem ein, um die erhobenen Designanforderungen zur Reduktion kognitiver Arbeitslast zu validieren. Unsere Ergebnisse zeigen, dass die Arbeitsbelastung durch den Einsatz von Assistenzsystemen reduziert wird. Im Anschluss untersuchen wir, wie kognitive Arbeitsbelastung visualisiert werden kann. Wir stellen eine Implementierung einer Biofeedback-Visualisierung vor, die das Nutzerverständnis zum Verlauf und zur Entstehung von kognitiver Arbeitslast unterstützt. Eine abschließende Studie zeigt, wie Messungen kognitiver Arbeitslast zur Vorhersage der aktuellen Leseeffizienz benutzt werden können. Wir schließen hierbei mit einer Reihe von Applikationen ab, welche sich kognitive Arbeitslast als Eingabe zunutze machen. Die vorliegende wissenschaftliche Arbeit befasst sich mit dem Design von Assistenzsystemen, welche die kognitive Arbeitslast der Nutzer implizit erfasst und diese bei der Durchführung alltäglicher Aufgaben unterstützt. Dabei werden physiologische Daten erfasst, um Rückschlüsse in Realzeit auf die derzeitige kognitive Arbeitsbelastung zu erlauben. Anschließend werden diese Daten analysiert, um dem Nutzer strategisch zu assistieren. Das Ziel dieser Arbeit ist die Erweiterung neuartiger und bestehender kontextbewusster Benutzerschnittstellen um den Faktor kognitive Arbeitslast. Daher werden in dieser Arbeit arbeitslastbewusste Systeme und arbeitslastbewusste Benutzerschnittstellen als eine zusätzliche Dimension innerhalb des Paradigmas kontextbewusster Systeme präsentiert. Wir stellen acht Forschungsstudien vor, um die Designanforderungen und die Implementierung von kognitiv arbeitslastbewussten Systemen zu untersuchen. Schließlich stellen wir unsere Vision von zukünftigen kognitiven arbeitslastbewussten Systemen und Benutzerschnittstellen vor. Durch die knappe Verfügbarkeit öffentlich zugänglicher Datensätze, Referenzimplementierungen, und Methoden, waren Kontextbewusste Systeme in der Auswertung kognitiver Arbeitslast bezüglich der Nutzerinteraktion limitiert. Ergänzt durch die in dieser Arbeit gesammelten Datensätze erwarten wir, dass diese Arbeit den Weg für methodische und technische Werkzeuge ebnet, welche kognitive Arbeitslast als Faktor in das Kontextbewusstsein von Computersystemen integriert

Resource-aware plan recognition in instrumented environments

This thesis addresses the problem of plan recognition in instrumented environments, which is to infer an agent';s plans by observing its behavior. In instrumented environments such observations are made by physical sensors. This introduces specific challenges, of which the following two are considered in this thesis: - Physical sensors often observe state information instead of actions. As classical plan recognition approaches usually can only deal with action observations, this requires a cumbersome and error-prone inference of executed actions from observed states. - Due to limited physical resources of the environment it is often not possible to run all sensors at the same time, thus sensor selection techniques have to be applied. Current plan recognition approaches are not able to support the environment in selecting relevant subsets of sensors. This thesis proposes a two-stage approach to solve the problems described above. Firstly, a DBN-based plan recognition approach is presented which allows for the explicit representation and consideration of state knowledge. Secondly, a POMDP-based utility model for observation sources is presented which can be used with generic utility-based sensor selection algorithms. Further contributions include the presentation of a software toolkit that realizes plan recognition and sensor selection in instrumented environments, and an empirical evaluation of the validity and performance of the proposed models.Diese Arbeit behandelt das Problem der Planerkennung in instrumentierten Umgebungen. Ziel ist dabei das Erschließen der Pläne des Nutzers anhand der Beobachtung seiner Handlungen. In instrumentierten Umgebungen erfolgt diese Beobachtung über physische Sensoren. Dies wirft spezifische Probleme auf, von denen zwei in dieser Arbeit näher betrachtet werden: - Physische Sensoren beobachten in der Regel Zustände anstelle direkter Nutzeraktionen. Klassische Planerkennungsverfahren basieren jedoch auf der Beobachtung von Aktionen, was bisher eine aufwendige und fehlerträchtige Ableitung von Aktionen aus Zustandsbeobachtungen notwendig macht. - Aufgrund beschränkter Resourcen der Umgebung ist es oft nicht möglich alle Sensoren gleichzeitig zu aktivieren. Aktuelle Planerkennungsverfahren bieten keine Möglichkeit, die Umgebung bei der Auswahl einer relevanten Teilmenge von Sensoren zu unterstützen. Diese Arbeit beschreibt einen zweistufigen Ansatz zur Lösung der genannten Probleme. Zunächst wird ein DBN-basiertes Planerkennungsverfahren vorgestellt, das Zustandswissen explizit repräsentiert und in Schlussfolgerungen berücksichtigt. Dieses Verfahren bildet die Basis für ein POMDP-basiertes Nutzenmodell für Beobachtungsquellen, das für den Zweck der Sensorauswahl genutzt werden kann. Des Weiteren wird ein Toolkit zur Realisierung von Planerkennungs- und Sensorauswahlfunktionen vorgestellt sowie die Gültigkeit und Performanz der vorgestellten Modelle in einer empirischen Studie evaluiert

Interpretation of Natural-language Robot Instructions: Probabilistic Knowledge Representation, Learning, and Reasoning

A robot that can be simply told in natural language what to do -- this has been one of the ultimate long-standing goals in both Artificial Intelligence and Robotics research. In near-future applications, robotic assistants and companions will have to understand and perform commands such as set the table for dinner'', make pancakes for breakfast'', or cut the pizza into 8 pieces.'' Although such instructions are only vaguely formulated, complex sequences of sophisticated and accurate manipulation activities need to be carried out in order to accomplish the respective tasks. The acquisition of knowledge about how to perform these activities from huge collections of natural-language instructions from the Internet has garnered a lot of attention within the last decade. However, natural language is typically massively unspecific, incomplete, ambiguous and vague and thus requires powerful means for interpretation. This work presents PRAC -- Probabilistic Action Cores -- an interpreter for natural-language instructions which is able to resolve vagueness and ambiguity in natural language and infer missing information pieces that are required to render an instruction executable by a robot. To this end, PRAC formulates the problem of instruction interpretation as a reasoning problem in first-order probabilistic knowledge bases. In particular, the system uses Markov logic networks as a carrier formalism for encoding uncertain knowledge. A novel framework for reasoning about unmodeled symbolic concepts is introduced, which incorporates ontological knowledge from taxonomies and exploits semantically similar relational structures in a domain of discourse. The resulting reasoning framework thus enables more compact representations of knowledge and exhibits strong generalization performance when being learnt from very sparse data. Furthermore, a novel approach for completing directives is presented, which applies semantic analogical reasoning to transfer knowledge collected from thousands of natural-language instruction sheets to new situations. In addition, a cohesive processing pipeline is described that transforms vague and incomplete task formulations into sequences of formally specified robot plans. The system is connected to a plan executive that is able to execute the computed plans in a simulator. Experiments conducted in a publicly accessible, browser-based web interface showcase that PRAC is capable of closing the loop from natural-language instructions to their execution by a robot

Advancement in Dietary Assessment and Self-Monitoring Using Technology

Although methods to assess or self-monitor intake may be considered similar, the intended function of each is quite distinct. For the assessment of dietary intake, methods aim to measure food and nutrient intake and/or to derive dietary patterns for determining diet-disease relationships, population surveillance or the effectiveness of interventions. In comparison, dietary self-monitoring primarily aims to create awareness of and reinforce individual eating behaviours, in addition to tracking foods consumed. Advancements in the capabilities of technologies, such as smartphones and wearable devices, have enhanced the collection, analysis and interpretation of dietary intake data in both contexts. This Special Issue invites submissions on the use of novel technology-based approaches for the assessment of food and/or nutrient intake and for self-monitoring eating behaviours. Submissions may document any part of the development and evaluation of the technology-based approaches. Examples may include: web adaption of existing dietary assessment or self-monitoring tools (e.g., food frequency questionnaires, screeners) image-based or image-assisted methods mobile/smartphone applications for capturing intake for assessment or self-monitoring wearable cameras to record dietary intake or eating behaviours body sensors to measure eating behaviours and/or dietary intake use of technology-based methods to complement aspects of traditional dietary assessment or self-monitoring, such as portion size estimation