assignment 2 empirical evaluation of a new website design

Identifying User Groups and Their ChallengesThe ''''Cookery'''' AI Chatbot cooking assistant is designed to cater to a diverse user population with varied cookinginterests, skill levels, time

ASSIGNMENT 2

Empirical Evaluation of a new Website designCourse: User-centered Design

Course code: COSC2652

Practical Tutor/

ID

Table of Contents

I.Introduction 4

1.Scenario Introduction and Problem Definition 4

2.Proposed AI Solution 4

II.User Analysis and Task Definition 4

1.Identifying User Groups and Their Challenges 4

2.Task Analysis and AI Solution Application 5

3.Usability Requirements and Target Levels 5

III.Prototype Design and Specification 5

2.Identification of Flaws or Misconceptions 8

V.Empirical Evaluation and Testing 9

VI.Data Analysis and Insights 12

1.Quantitative Data Analysis 12

a Users’ Performance Test 12

b Concepts Evaluation 12

2.Qualitative Data Analysis 13

a Survey Approach 13

b Face-to-Face Interview Approach 13

3.Post-Testing Heuristic Analysis Findings and Conclusions 13

VII.Modifications Based on Evaluation 14

1.Identify Modifications 14

2.Plan for Implementing Modifications 14

VIII Reflections 15

1.Team’s Strategy 15

2.Our Strengths, Weaknesses & Challenges 15

3.Lessons Learned and Future Applications 16

REFERENCES 17

APPENDICES 18

Appendix A: User Groups 18

Appendix B: Personas 21

Appendix C: Task Analysis and AI Solution Application 23

Appendix D: Usability Requirements and Target Levels 25

Appendix E: ‘Cookery’ Prototype 26

Appendix F: Usability Assessment 27

Appendix G: Empirical Evaluation Preparation 29

Appendix H: Quantitative Data Analysis 31

Appendix I: Qualitative Data Analysis 34

Appendix J: Modifications Based on Evaluation 38

Appendix J: Team’s Strategy 39

1 Scenario Introduction and Problem Definition

In the wake of the global pandemic, one significant lifestyle transformation has been our relationship with food.Dining habits worldwide have been affected, with a distinctive shift towards home-cooked meals This trend isnot merely anecdotal but is supported by hard data According to a Nielsen report (2020), the worldwide homecooking rate rose by 60% during the pandemic, and Vietnam mirrored this trend with a surge in home cookingdocumented by VNExpress (2020).

The rise in self-cooking, while indicative of a healthier and potentially more satisfying approach to food, hasalso underscored some considerable challenges The process of self-cooking is often time-consuming andcomplex, necessitating a myriad of decisions such as what to cook, procuring the ingredients, and following arecipe accurately Moreover, considerations around dietary restrictions, nutritional balance, and personal tastepreferences add another layer of complexity to the task This scenario provides a compelling opportunity toinvestigate how technology, specifically AI-Chatbot technology, could be used to improve this situation,making the process of self-cooking more streamlined, enjoyable, and accessible.

2 Proposed AI Solution

To address these challenges, we propose a solution: 'Cookery', an AI-Chatbot cooking assistant This tool aimsto provide users with personalized recipe recommendations based on their preferences and availableingredients, offer easy-to-follow cooking instructions, and answer any food-related queries in real time In thesubsequent sections of this report, we detail the design, development, and evaluation plan of our proposedsolution.

The ultimate objective is to improve the overall self-cooking experience, by making it more streamlined,engaging, and less stressful, all of which aligns with our commitment to enhancing daily life throughinnovative AI technology.

II.User Analysis and Task Definition

1 Identifying User Groups and Their Challenges

The 'Cookery' AI Chatbot cooking assistant is designed to cater to a diverse user population with varied cookinginterests, skill levels, time constraints, and dietary needs Identifying the different groups within this population,along with their distinct goals, both generic and specific, and challenges can significantly contribute to tailoringthe AI-Chatbot's functionalities and features to enhance these users' cooking experiences.

Appendix A provides detailed information about the four primary user groups that are likely to interact with'Cookery': Novice Cooks, Health-Conscious Cooks, Busy Professionals, and Culinary Enthusiasts Theircharacteristics, values, requirements, goals, and potential challenges that they might face are elaborated inTable

1,Table 2,Table 3, andTable 4respectively.

Personas: We have developed comprehensive personas to represent four main user groups: Novice Cooks,

Health-Conscious Cooks, Busy Professionals, and Culinary Enthusiasts, providing a deeper understanding oftheir unique challenges and requirements, as shown inFigure 1,Figure 2,Figure 3, andFigure 4in Appendix B.

2 Task Analysis and AI Solution Application

To maximize the effectiveness of the 'Cookery' AI-Chatbot cooking assistant across our diverse user base, acomprehensive task analysis is crucial This involves delineating the specific tasks that each user group needs toaccomplish and understanding how our AI solution can be employed to facilitate these tasks.

Detailed information on the tasks for each user group, along with the corresponding applications of the'Cookery' AI solution, is provided in Appendix C, as outlined inTable 5.

3 Usability Requirements and Target Levels

For the prototype stage of the 'Cookery' AI-Chatbot cooking assistant, it is essential to establish usabilityrequirements and target levels These benchmarks cater to each user group and serve as a developmental guide,helping to shape 'Cookery' as it progresses.

Detailed information on the usability requirements and target levels for each user group can be found inAppendix D, as outlined inTable 6.

III Prototype Design and Specification

1 Prototype Overview

The 'Cookery' AI-Chatbot prototype focuses on testing AI's effectiveness in delivering personalized reciperecommendations versus traditional search methods The goal is a tailored, efficient cooking experience basedon individual preferences.

The prototype works by offering a selection of cooking preferences Users input their choices, and the AIChatbot uses this to suggest personalized recipes Users can review and refine these recommendations, leadingto a more precise recipe.

Our prototype, built on a static website framework using HTML, CSS, and JavaScript, delivers an interactiveand authentic testing experience A minimalist design approach and controlled input options emphasize theChatbot's efficiency in providing personalized recipes.

Please note, this prototype is a testing phase product for evaluating AI Chatbot performance, not a final product.It's a key step towards user needs comprehension and solution refinement Here is the link to our prototypewebpage: https://snitcoding.github.io/Cookerynoserver/ Please refer to Figure 5 in Appendix E for ademonstration of the ‘Cookery’ prototype main page.

2 Design Specification

a UI Design Principles

The design of our ‘Cookery' AI-Chatbot cooking assistant prototype centers on functionality We aim toprovide a user interface that supports easy interaction with the AI tool, focusing on its operation and benefits,while also prioritizing accessibility, readability, and user comfort.

The following provides an overview of the key UI design principles applied to the prototype:

 Font Family: We selected Arial, sans-serif, a universally readable font compatible with diverse devices and

operating systems, in line with our design objective.

 Font Sizes: We use a font size of 1.2rem for general text and 2.5rem for headers, ensuring legibility across

various screen sizes and resolutions Headers stand out, guiding user navigation.

 Line Height: Set at 1.6 to enhance readability, this spacing ensures clear differentiation between text lines.

 Accessibility and Comfort: We've prioritized accessibility, ensuring optimal text-background contrast, and

incorporated hover/focus outlines for clear visual cues.

Our design's simplicity allows users to focus on the tool's functionality, while its accessibility and comfort arenot compromised As the prototype evolves, these principles will be refined based on user feedback, reinforcingour commitment to enhancing the 'Cookery' user experience.

b UX Design Strategy

Our User Experience (UX) design strategy for the 'Cookery' AI-Chatbot aims to provide a streamlined and friendly environment The design facilitates simplified interaction and delivers personalized reciperecommendations.

user-Users are presented with nine predefined cooking reference options, encompassing a variety of cookingpreferences, to facilitate easy understanding and accessibility These options include four select boxes, threenumber inputs, and two free-text inputs, all of which are optional, allowing users to customize their input basedon their comfort.

After users define their preferences, the AI Chatbot generates a tailored recipe Users can fine-tune the recipethrough additional instructions to the Chatbot, iteratively refining it until it aligns with their preferences.Our UX design caters to users of varying cooking skills and culinary knowledge, ensuring even those withminimal experience can successfully use the tool Ultimately, the design aims to make recipe discovery andcooking more enjoyable and less intimidating for all users.

c AI Integration Methodology

To enhance the authenticity of our prototype during testing, we've integrated it with the reputable ChatGPT AI,

selected after thorough analysis OpenAI's comprehensive documentation and resources have been instrumentalin our effective use of the ChatGPT API and in crafting bespoke prompts.

We've adopted a pure JavaScript implementation for ChatGPT integration, prioritizing cost-efficiency Thismethod, involving direct API calling and dynamic webpage text addition, removes the need for extradependencies like NodeJS or Python and their required libraries.

Additionally, this methodology facilitates straightforward deployment on GitHub Pages, bypassing the need forserver or domain setup, or complex procedures This choice balances AI integrity and functionality with smoothdevelopment, highlighting our dedication to an effective, accessible, user-centric solution.

IV Interactive Prototype Evaluation

1 Usability Assessment

a Heuristic Evaluation

In the process of conducting a comprehensive evaluation of our interactive prototype, we have utilized theHeuristic Evaluation method Developed by Jakob Nielsen, this method of usability inspection provides a set ofestablished principles for evaluating the interface design of interactive systems (Nielsen, 1994) Here, wepresent a detailed Heuristic Evaluation of our prototype based on Nielsen's Heuristics:

 Visibility of system status: The Cookery AI Chatbot provides immediate feedback on the users' actions.

Whenever a user inputs a command or a request, the chatbot responds promptly, keeping users informedabout what's happening.

 Match between the system and the real world: The language used by the Cookery AI Chatbot is simple,

clear, and familiar The use of culinary terms and the presentation of the recipes align with the real-worldcooking experience.

 User control and freedom: Users can easily navigate through their conversation with the AI-Chatbot, edit

their preferences, or exit the chat at any point There's a strong sense of user control and freedom.

 Consistency and standards: The user interface of the Cookery website maintains a consistent design

throughout The language and interaction patterns remain uniform across the platform.

 Error prevention: The Cookery system is designed with a structured and controlled input format, which

reduces the likelihood of user errors Moreover, the AI-Chatbot can handle a variety of user inputs withoutgenerating errors.

 Recognition rather than recall: The prototype supports recognition over recall by presenting users with

selectable options for their cooking preferences, rather than requiring them to remember and type theirchoices.

 Flexibility and efficiency of use: The Cookery prototype caters to both novice and experienced users The

system allows users to specify their preferences in detail, leading to a more personalized and efficientexperience.

 Aesthetic and minimalist design: Cookery follows a minimalist design philosophy The user interface is

clean and simple, focusing on the essential features and minimizing potential distractions.

 Help users recognize, diagnose, and recover from errors: In case of unexpected user input, the

AI-Chatbot provides a polite and clear error message, guiding users to input correctly.

 Help and documentation: The Cookery prototype provides a brief guide on how to interact with the

AI-Chatbot, ensuring that users have the necessary information to use the system effectively.

b Cognitive Walkthrough

The task of finding a personalized recipe using the Cookery AI-Chatbot is the most suitable task for a detailedcognitive walkthrough It is pertinent to a broad user spectrum, and it comprises several steps, potentiallyrevealing a wide array of usability aspects The task will be segmented into a series of steps onTable 7inAppendix F, which will be evaluated using The Four Questions of Cognitive Walkthrough as articulatedWharton et al (1994):

 Will the user try to achieve the right effect?

 Will the user notice that the correct action is available?

 Will the user associate the correct action with the effect they're trying to achieve?

 If the correct action is performed, will the user see that progress is being made toward the solution of theirtask?

Test Scenario: Consider a user named Alex, a 25-year-old novice cook who wants to prepare a meal with the

ingredients he has at home He decides to use the Cookery AI-Chatbot to find a recipe that matches hispreferences and the ingredients he has on hand.

 Alex has access to a computer with an internet connection. Alex is familiar with using web browsers.

 Alex is fluent in English and is comfortable navigating websites for information.

2 Identification of Flaws or Misconceptions

The prototype's current design presents several areas of potential confusion or difficulty for users, particularlythose who are new or less experienced with such platforms The task steps within the workflow lack clear visual

markers or distinct delineations, such as sequential numbering or explicit indications of progress This absencecould lead to users feeling overwhelmed or confused, particularly given the numerous input options available onthe screen As a result, users may navigate through the form more slowly, and their understanding of thefunctionality might be compromised This lack of clarity could contribute to unnecessary time consumption andpotentially undermine the user experience.

Furthermore, the prototype does not provide clear indicators of the user's current progress within the form Theabsence of a visible indication of progress may leave users uncertain about whether their inputs have beensuccessfully registered or if modifications to the recipe have been adequately implemented This uncertaintycould lead to user dissatisfaction and a perceived lack of control over the process.

While the aim of providing a variety of cooking references is to enhance user convenience, some of theseoptions might be unclear to users without a certain level of culinary knowledge Even though all fields areoptional, the need for users to conduct additional research to understand these cooking-related aspects couldintroduce an unintended complexity into the system.

Finally, the prototype incorporates the ChatGPT Chatbot, renowned for its flexibility and versatility However,its unrestricted free text input capability might offer users an unintended degree of freedom, potentiallyallowing them to interact with the system in ways that were not originally envisaged This broad scope ofinteraction could lead to misuse or exploitation of the system, deviating from its intended purpose ofpersonalized recipe generation.

V.Empirical Evaluation and Testing

1 Preparation

a Subjects (Participants)

Our empirical evaluation and testing process incorporates five participants, representative of the four primaryuser groups identified in our user analysis This approach allows our evaluation to reflect a diverse set of userexperiences, expectations, and behaviors.

Two participants, a student and a young professional aged 16-35, represent the 'Novice Cooks' group Theirshared attributes include less confidence in cooking, a desire to learn, and time constraints Their primarychallenges involve understanding ingredients, following complex instructions, and efficient meal planning.The 'Health-Conscious Cooks' group is represented by a professional aged 25-65+, interested in maintaining abalanced diet and finding recipes that meet specific dietary needs.

The fourth participant, a 'Busy Professional' aged 25-60, prioritizes efficiency and convenience due to workcommitments, and often seeks quick, healthy meal options.

The final participant, aged 18-65+, symbolizes the 'Culinary Enthusiasts' group Passionate about cooking and

exploring new recipes, this participant often seeks unique or specific cuisine recipes and appreciates advancedcooking techniques.

b Consent Form

Our commitment to ethical principles and guidelines in the context of user research involving humanparticipants is paramount Consequently, we have developed a detailed Consent Form This document outlinesthe specifics of the study, what participants can expect, and how we will prioritize their confidentiality andanonymity throughout the research process Please follow the attached link to access and review the full contentof the Consent Form:Consent Form Document.

c Task Guide Documents

To facilitate a systematic and thorough testing process, a comprehensive task guide document has been prepared.This document delineates the step-by-step procedure to be followed during the evaluation of the Cookery AIChatbot, ensuring consistency across all test sessions For a detailed understanding of the testing protocol,please refer to the link provided:Test Guide Document

d Tasks Preparation

Before proceeding with the empirical evaluation of the Cookery AI Chatbot, it's crucial to have a systematicplan for task preparation This helps to ensure that the user testing is effective and that we gather the mostvaluable and relevant information possible about the user experience Further elaboration on each task, itspurpose, and expected outcomes from the participants is available inTable 8in Appendix G.

e Roles, Facilitators, and Responsibilities

For the smooth functioning of the user testing process of the Cookery AI Chatbot, each member has beendesignated a specific role These roles are crucial for systematically and efficiently conducting the evaluation,and each role has distinct responsibilities For a detailed overview of each role, its responsibilities, and theassigned team members, please refer toTable 9in Appendix G.

2 Evaluation

a Testing Environment Setup

The evaluation is to be conducted in a controlled environment, free from external interruptions and noise Thisensures that the participants can focus entirely on interacting with the Cookery AI Chatbot A computer with astable internet connection is required, and the participants will be able to access the prototype through theprovided URL All necessary preparations including the prototype launch and printing of consent forms aremanaged by Tin Huynh.

b Testing Methodology

Our testing methodology employs a combination of established user testing techniques to gain an insightful and

comprehensive understanding of the user experience with the Cookery AI Chatbot Here are the primarymethods used:

Think-Aloud Protocol: Participants are encouraged to think aloud as they interact with the Cookery AI Chatbot.

This technique enables us to gain insights into the participant's thought processes, understand their expectations,and identify any confusion or challenges they encounter while performing the tasks.

Task-Based Testing: Participants perform a sequence of 12 interrelated tasks designed to mimic typical user

interactions with the AI system Each task evaluates a different functionality of the Cookery AI Chatbot, such asits ability to suggest recipes based on user preferences, manage dietary restrictions, work within budgetconstraints, and more The purpose of task-based testing is to assess the tool's effectiveness in a practical, real-world context.

Concurrent Observation: As participants interact with the chatbot, observers carefully document their actions,

reactions, difficulties, and successes This includes both verbal feedback through the Think-Aloud protocol andnon-verbal cues like hesitation or confusion.

Post-task Interviews: After each task, participants are asked to share their feedback on the task, the chatbot's

responses, and the overall interface This feedback is critical for understanding their experiences, identifyingpotential improvements, and assessing the user-friendliness of the tool.

c Execution of Testing

1 Introduction and Consent: The test begins with a brief introduction from the facilitator (Subject Handler),

explaining the purpose of the test and reassuring the participant that it's the system being evaluated, not them.The facilitator then presents the consent form and ensures that the participant understands and agrees with itscontent before signing.

2 Task Explanation and Prototype Interaction: The facilitator (Prototype Manager) hands out the task

document to the participant, explaining each of the tasks that they will be performing The participant is thendirected to the AI chatbot interface, where they will interact with the system and perform the outlined tasks.Throughout the interaction, participants are encouraged to think aloud and express their thoughts, feelings,and questions.

3 Observation and Data Tracking: During the interaction, the Data Tracker keeps a careful record of the

participant's actions, reactions, struggles, and successes They note down any areas where the participantseems to be confused or makes errors This concurrent observation provides critical insights into the system'susability.

4 Post-task Discussion and Debriefing: After each task, the Subject Handler asks the participant questions

related to their experience with that task, allowing them to provide immediate feedback At the end of alltasks, the Subject Debriefer conducts a more in-depth interview with the participant, discussing their overall

experience, any difficulties they encountered, and any improvements they suggest.

5 Evaluation Completion: Once the interview is completed, the participant is thanked for their time and

valuable feedback All collected data, including observation notes, task completion rates and times,participant responses, and video recordings, are then gathered and prepared for the analysis stage.

We've recorded one of our testing sessions, the video provides a detailed and realistic perspective of how theevaluation unfolded, the interaction of the participant with the Cookery AI Chatbot, and how our team handledvarious responsibilities during the evaluation process Here’s the link to the video:

d Findings

Following the execution of the evaluation, the next crucial step is to collate, examine, and analyze the collecteddata This process enables us to gather vital insights about the participants' interactions with the Cookery AIChatbot, understand their experiences, and identify the strengths and potential areas for improvement of the AItool The findings section will broadly categorize the results into two types:

Quantitative Findings: This will primarily involve the numerical data obtained during the evaluation process.

Metrics such as task completion rate, task completion time, error rate, and other measurable elements fall underthis category This data provides concrete evidence of the tool's performance, usability, and efficiency from anumerical standpoint.

Qualitative Findings: This segment of findings will encompass the subjective responses and feedback obtained

from the participants Observations made during the 'Think Aloud' protocol, responses to the post-testinterviews, and subjective opinions on the AI tool's interface, functionality, and overall experience belong tothis category.

VI Data Analysis and Insights

1 Quantitative Data Analysis

a Users’ Performance Test

For an in-depth understanding of the user interactions and performances with our AI Cooking Assistant, refer to

Table 10in Appendix H This detailed evaluation showcases essential metrics like task completion time, errorrate, and misconception rate, providing valuable insights for optimizing the system's user experience.

b Concepts Evaluation

Our analysis of the test data also included a systematic evaluation of three key concepts: completion time, errorrate, and misconception rate These parameters were derived from our initial test design and played a significantrole in assessing the system's performance across different user categories A summary of our findings ispresented inTable 11below in Appendix H Please refer to it for a detailed analysis.

2 Qualitative Data Analysis

a.Survey Approach

Online survey:

In addition to our performance testing, we employed a qualitative data collection method to gain deeper insightsinto the user experience Specifically, we utilized an online survey via Google Forms, which enabled us togather detailed feedback from our users The survey form can be accessed at this link:Survey

Response results:

The responses we received provided valuable insights into user sentiment and perceptions about our AI cookingassistant Please refer toFigure 6,Figure 7,Figure 8 Figure 9 Figure 10, , ,Figure 11,Figure 12, andFigure 13inAppendix I for an overview of the responses we collected.

b Face-to-Face Interview Approach

In order to gather more personal and nuanced information about user impressions and usability, we conducted aseries of face-to-face interviews Common responses to our questions underscored both strengths and potentialareas for improvement in our design For a summary of the questions asked and the common responses wereceived, please refer toTable 12in Appendix I.

3 Post-Testing Heuristic Analysis Findings and Conclusions

Upon concluding our user testing, we conducted a thorough heuristic analysis based on Nielsen's principles.This review incorporated both our perspective as designers and the feedback received from users to provide aholistic evaluation of the AI Cooking Assistant's usability and design.

 Aesthetic and Minimalist Design: The interface's minimalist design was well-received by users, who

appreciated the low-fidelity approach and the straightforward presentation of information.

 Ease of Use: The low technical skill requirement for operating the interface was another strength Users

could navigate the interface and utilize its functionalities effectively with just basic mouse and keyboardskills.

 Efficiency: The system demonstrated efficiency in remembering old inputs and allowing users to select

options and adjust values using keyboard shortcuts, thereby speeding up the input process.

However, we also identified several areas where our interface fell short of Nielsen's heuristic principles:

 Visibility of System Status: Users expressed difficulty in identifying when the AI had completed the recipe

generation, particularly due to the lack of automatic scrolling or notifications The absence of clearindications about the user's progress also compounded this issue.

 Help and Documentation: The need for more detailed explanations and help was apparent, especially

regarding specific food references and inputs like 'Umami' for taste and currency for budget Users requiredadditional information to utilize these functionalities effectively.

 User Control and Freedom: The interface lacked options in certain contexts, such as taste preferences and

complexity of meals This restricted users' freedom and control, potentially affecting their overall satisfactionwith the system.

In light of these findings, we can conclude that while our AI Cooking Assistant has many strengths, there arecrucial areas of improvement that need to be addressed to enhance the overall user experience These insightswill guide our subsequent modifications and improvements to the system.

VII Modifications Based on Evaluation

1 Identify Modifications

The identification of usability issues and their subsequent modifications are crucial to improve the overall userexperience and performance of our AI Cooking Assistant To ensure a systematic approach, we used theNielsen Severity Rating Scale This scale ranges from 0 to 4 to rate the severity of usability problems:0 = I don't agree that this is a usability problem at all

1 = Cosmetic problem only: need not be fixed unless extra time is available on project2 = Minor usability problem: fixing this should be given low priority

3 = Major usability problem: important to fix, so should be given high priority4 = Usability catastrophe: imperative to fix this before product can be released

Our analysis of user interactions and responses during the testing phase resulted in the identification of fivemain issues onTable 13in Appendix J.

2 Plan for Implementing Modifications

Addressing the identified issues in a systematic and efficient manner is key to optimizing the user experience.Here's our proposed plan for implementing modifications:

Developing Guidance and Documentation: We will augment the system with comprehensive guides and

in-line help text for each input field This includes clarifying currency and time units for Budget and PreparationTime, respectively Contextual help icons can be added next to these input fields, providing users withnecessary guidance as they interact with the system.

Enhancing Taste Choice Descriptions: To help users make informed choices, we will provide clear and

detailed descriptions for each taste option This could be implemented as a hover-over tooltip text or a help iconnext to each choice, offering users an understanding of what each taste implies in a cooking context.

Introducing Translation Support: To bridge the language gap, we plan to integrate a translation feature,

especially for ingredient names and dietary restrictions This will involve mapping common ingredients anddietary terms to their equivalents in various languages We might also consider auto-suggest features tofacilitate user inputs in this context.

Clarifying Complexity Levels: To ensure users understand the complexity levels, we will include examples or

definitions for 'simple', 'intermediate', and 'advanced' levels These definitions will be presented in understand language and displayed in a way that does not clutter the interface, such as hover-over tooltip text.

easy-to-Improving Interface Interactions: To make the interface more interactive, we propose to add a loading icon

while the system processes the recipe We also plan to introduce automatic scrolling to direct users to the resultonce it's generated These changes aim to provide visual feedback to users about system operations and ensurethey do not miss any critical outputs.

VIII Reflections

1 Team’s Strategy

Our team decided to divide our process into 4 phases namely project planning, prototype designing,prototype developing, and empirical evaluation phase as detailed inTable 14,Table 15,Table 16, and

Table 17respectively in Appendix J

Our team's strength lies in the diverse skill set and extensive experience of our members Hau, Nam, Tin,Duong, and Nhan all bring unique talents to the table Hau, Nam, and Tin are proficient in website development.Nam and Tin, particularly, have substantial experience with AI technologies, and their insights were

instrumental in effectively integrating AI Chatbot technology into our project Tin took the lead on many of thetechnical tasks, providing crucial input and guidance that shaped the project's success On the analytical side,Duong and Nhan excelled in brainstorming sessions, providing substantial input to the project's structure Byutilizing our individual strengths and supporting each other's weaknesses, we achieved success in our project.

Weaknesses and Challenges:

Despite our strengths, we faced a range of challenges throughout the project The initial stage was particularlychallenging as we struggled to understand the project's requirements and objectives This necessitated numerousdrafts and consultations with our lecturer As most of us were more familiar with developing complete products

rather than prototypes, defining the concepts of low fidelity and high fidelity and integrating AI Chatbottechnology into our project interface was a significant hurdle Practical issues like understanding how toconduct an empirical evaluation test and the unexpected delays from test users added to the challenges.Communication was another challenge, with missed meetings and occasional misunderstandings, despite ouruse of Facebook and Messenger for team communication Additionally, the need to make our meetings moreefficient became apparent as some of them ran long with little outcomes due to distractions or members'unavailability.

3 Lessons Learned and Future Applications

Through the project, we gained a deeper understanding of the effective use of Chatbot AI, specifically ChatGPT.We learned how to elicit the desired responses and how to incorporate such technology into our applications orwebsites These are valuable skills that we can use in future projects.

We also improved our teamwork skills, with a particular focus on task specialization and efficientcommunication We grappled with issues like miscommunication and last-minute procrastination, especiallyduring the report preparation phase, which often led to delays These experiences underscored the importance ofclear communication, efficient time management, and working cohesively as a team.

Looking ahead, the knowledge and skills gained from this project will undoubtedly be beneficial in futureendeavors The insights we gained into AI Chatbot technology present exciting opportunities for developingmore interactive and intelligent applications Furthermore, the experiences and lessons we've gained regardingteamwork and project management will serve us well in our future group projects.

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https://www.nngroup.com/articles/how-to-rate-the-severity-of-usability-problems/(Accessed: 14 May 2023).

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(Accessed: 14 May 2023).

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4081284.html(Accessed: 14 May 2023).

https://e.vnexpress.net/news/news/covid-19-impact-vietnamese-rediscover-joy-of-eating-at-home-Wharton, C., Rieman, J., Lewis, C., & Polson, P (1994) 'The Cognitive Walkthrough Method: A Practitioner'sGuide', in Nielsen, J and Mack, R.L (eds.) Usability Inspection Methods John Wiley & Sons.

Specific Goals  Preparing a specific dish or cuisine Improving cooking skills

Table 1 ‘Novice Co oks ’ user group

Socio-Economic Status All ranges

Education Higher levels generally, but can also be variedCareers Professionals, health enthusiasts, fitness trainers

Personal Characteristics Interested in nutritional balance, might have specific dietary needs, committed

to a healthy lifestyle

Values Healthy eating, fitness, wellness

Requirements Nutritional information, recipes catered to specific dietary needs, meal planningassistance for balanced diets

Generic Goal Maintain or improve health

Specific Goals  Find and prepare nutritionally balanced meals. Adhere to specific dietary needs or restrictions

 Difficulty in finding recipes that meet specific dietary requirements. Struggle to calculate nutritional values and balance meals appropriately. Limited options or ideas for healthy recipes.

 Challenge in understanding the health benefits/risks of certainingredients or cooking methods.

Ta ble 2 ‘Health-Conscious Cooks ’ use r group

Socio-Economic Status Middle-class or above

Education Higher levels generally, but can also be variedCareers Professionals across different fields, entrepreneurs

Personal Characteristics Time-pressed, may value convenience, might have limited time for mealpreparation

Values Efficiency, time management, convenience

Requirements Quick and easy recipes, meal prep ideas, suggestions for healthy and quicksnacks

Generic Goal Save time in meal preparationSpecific Goals  Prepare meals ahead of time.

 Discover quick and easy recipes

Ta ble 3 ‘Busy Professionals ’ user grou p

Socio-Economic Status All ranges

Education All levels, may have specific culinary education

Careers Can be varied, including chefs, food bloggers, food critics, or simplyindividuals who love cooking

Personal Characteristics Passionate about cooking, interested in exploring new recipes and cuisines, mayhave advanced cooking skills

Values Creativity, culinary art, diversity in food

Requirements Wide variety of recipes, unique and authentic recipes, advanced culinarytechniques

Generic Goal Explore culinary arts

Specific Goals

 Try out diverse recipes. Learn new cooking techniques. Prepare a specific gourmet dish