Firstly we will briefly discuss the learning outcomes for the HCI 2 module and then provide a conclusion of our overall process which will show how the learning outcomes were satisfied. By all means this is not a comprehensive list of all our posts, so please take this into consideration.
Learning outcome 1: Explain and discuss practical and theoretical aspects of Human-Computer Interaction.
During the lifecycle of the project, we discussed both the theoretical aspects of HCI and its practicality which can be found here. We analyzed the theoretical aspects of creating persona's, conducting scenarios and designing prototypes as well as providing a mindmap for our target group.
Our case studies involved evaluating robotic component technology, to assess its suitability for integration into the Robot Teaching Assistant, which is the technology that is aimed at children.
We also considered factors such as ethics from attending Russell's lectures.
For more posts which satisfy this criteria, please see our conclusion below (after the learning outcomes)
Learning outcome 2: Apply HCI principles to practical problems.
Throughout the course of the project, we successfully applied the User-Centered Design process which is described in the conclusion below. To summaries, this involved creating persona's, scenarios, prototypes, questionnaires and a range of evaluation techniques.
For further reading which satisfies this criteria, please see our conclusion below (after the learning outcomes)
Learning outcome 3: Participate in analysis and design work in HCI.
We have fulfilled this criteria which is evident in our conclusion below.
Our Conclusion
The blog was created to comply with the Human Computer Interaction II module at the School of Computer Science. During the lifecycle of the project, our aim was to produce a new innovative tool that would help in assisting children at school, by going through the User-Centered Design process. This involved a continuous feedback loop which kept going back to the user – the persona's – (Serena, Ben, Tom, Jason).
We firstly began by forming a mind-map of the under 11 age group, this helped us to see what perceptions the group had for the under 11 age group. Furthermore, we then conducted a brainstorming session, in which the group suggested various ideas and were filtered over two stages. We then created a number of persona's a variety of children in our target audience (Under 11) to aid in the process of finalizing our prospective idea. During the persona stage, it was decided that two of the persona's were to be real and two to be imaginary to ensure that the process was applicable in the real world.
After the persona's, we then finalized our final idea which was the Robot Teaching Assistant. We decided that this was the most innovative and interactive of the ideas suggested, and furthermore, taking into account the rate of technology adoption in the educational sector, the project provided motivation. We carried out an analysis of the market. At this point we were faced with a major design decision, whether the teaching assistant should have a humanoid or robotic appearance.
After this, we then derived the requirements from analyzing the persona's. We began to develop scenarios in order to aid in the development process. The scenarios involved the persona's and observing their current educational environment in order to gain knowledge on how the Robot Teaching Assistant would interact in those environments.
Throughout the process, a number of case studies were conducted which researched into current robotic technologies and components that can be used in our prototype. This enabled us to create the creative design (and more designs here) of the teaching assistant based on the initial requirements gathered from analyzing the persona's. The creative design was important as it allowed us to create an initial prototype based on the needs of the persona's from assessing both the scenarios and persona's. Through discussion and evaluation of the requirements at the creative design stage, the first prototype was created named Miss Dawson. After the prototype was developed, testing and evaluation was conducted on these components:
- Video / Visual
- Audio
- Picture Quality
The next stage of our evaluation was to put the prototype in the scenarios described previousely to observe how the first prototype interacted with the persona's in the scenario using questionnaires. After the testing and evaluation on the prototype, we carried out a critical appraisal of the prototype which led to refinements (part of the redesign stage) being made in our redesign called iBot.
The redesign reflected the issues that were raised in the testing / evaluation of the first prototype based upon the persona's reactions in the scenarios. To assess the redesign, a number of evaluation techniques were considered. From this, we selected the heuristic evaluation and cooperative evaluation. The cooperative evaluation allowed the persona's to raise questions about iBot to the designers and allowed us to observe the persona's interactions with the iBot. The heuristic evaluation involved assessing iBot against a number heuristics. Furthermore, from our evaluations, we conducted a further assessment of any further refinements based upon the evaluations conducted in the previous stage.
To conclude we managed to create “iBot” using the user-centered design approach. As a group, we feel that we have fulfilled this to an extent, however, there are criticisms. During the project, we did make a number of assumptions, for example, that AI technology was so advanced that it could detect human emotions and that some of the components discussed in our cases were readily available. In relation to the User-Centered Design process, we felt that if we had a bit more time we could have conducted further investigations regarding the end user, which would aid in helping us understand more the needs of our target group. We have followed the user centered design process and feel that the process conducted has resulted in a technology being developed that our target group will use.