IS480 Team wiki: 2015T1 Vulcan Final
|HOME||ABOUT US||PROJECT OVERVIEW||PROJECT MANAGEMENT||DOCUMENTATION|
- 1 Project Progress Summary
- 2 Project Management
- 3 Schedule Metric Formula: (Estimated Days / Actual Days) x 100%
- 4 Quality of product
- 5 Reflection
Project Progress Summary
File:IS480 Vulcan Mid Term Presentation.pdf***************
Highlights of Project:
- LiveLabs relocation of servers on Oct 5th 2015, two days before Midterms Presentation
- LiveLabs servers overload (data increase 1GB/minute), root cause remains unknown
- Delay in SMU IRB's approval and migration to Production server, Vesta
- Server hosting the ReFokus Mobile App was disabled for an hour during the Pilot Study phase
Challenges of Project:
- Picking up mobile application development skills in Android
=> Google, stackoverflow was our best friend!
- Understanding of server administration and configuration, eg. reversed proxy and session forwarding
=> Be confident of own codes! When in doubt, clarify!
- Understanding the concept of mindfulness and data collection for research studies
=> Understanding of concept helps us think better like the end user. Fun Fact: Now, we are all IRB certified to collect data!
Achievements of Project:
- First undergraduate project to be launched on LiveLabs production server, Vesta
- Successfully integrated smart wearable health vital monitoring function to the mobile application for research purposes
Note: Though we had achieved 100% completion for our project (based on planned scope) & we had conducted a handover session with our sponsor, we are still working to refine on the User Interface to provide better user experience :)
Please refer to Planned vs Actual Tasks Metrics for the detailed breakdown of our individual tasks.
Project Schedule (Plan Vs Actual):
Based on the planned schedule, after midterms we have discussed with our sponsor and supervisor and decided to drop some functions and reschedule to focus more on testing to ensure that the functions in core and secondary scope are working well. After midterms, our iterations were all 100% on schedule.
Planned Schedule (Mid Term)
Schedule Metric Formula: (Estimated Days / Actual Days) x 100%
|Iteration||Planned Duration (Days)||Actual Duration (Days)||Schedule Metric Score||Action||Status|
|2||18||32||56.25%||Team is behind schedule. This is due to the complexity of the tasks planned (Android App and Smart Watch).
Follow up action: Rescheduled the future iterations, deducted days from buffer days.
|4||18||24||75%||Team is behind schedule. This is due to Livelab's server permission issues.
Follow up action: Rescheduled the future iterations, deducted days from buffer days.
These are the top risks we have identified and has occurred during our project. We have followed the mitigation steps listed above and successfully managed the risks.
Beeper Survey Creation:
Beeper surveys are created each day by an alarm manager using the set method. The setWindow method was initially used as it would schedule the alarm within a given window of time. However, this did not ensure that participants received beeper surveys at a random times because the beeper surveys would go off close to the start time. In order to fix this problem, the randomisation of beeper timings was done beforehand through java. This was done because there was no method to implement what the sponsor wanted which was 3 random beeper surveys each day with the timings being all different.
There will be 3 blocks of equal duration created based on the wake up time and sleep time which the participant has inputed. From there, 3 random numbers will be generated with the max number being the length of a block. These 3 numbers will be added to the start time, block 1 time and block 2 time to create the 3 random times for the beeper surveys.
Android Studio's alarm manager does not allow repeating alarms to have a different time everyday and thus this could not be used. The solution from our team was to create a repeating alarm that will go off at midnight if the participant's sleep time is before midnight and at the sleep time if the participant's sleep time is after midnight. The repeating alarm will call the BeeperCreator class which creates the 3 random beeper survey timings for the day.
Dynamic generation of survey elements:
Normally to implement dynamic lists of content, we would use the Android ListView to display the elements on the activity page. ListView is useful for creating a scrolling list of elements that can be interactable and is efficient in terms of implementation. However, due to how ListView recycles elements that move out of view when scrolling, it is difficult to retain user entered information that is linked to an element, as the information would be inherited by the "new" element that comes into view.
To avoid this, we implement ScrollView instead. ScrollView is useful for showing a scrolling page of static elements but its not usually used to generate a dynamic list. The above shown implementation indicates how we append a layout "fragment" to the current ScrollView to represent a single survey question element. We populate the question fields for each question element and attach it to the view, allowing a scrolling view that will display questions according to what is required for this particular survey. All question elements are active in memory and are set up to collect user input as indicated in the implementation below.
Quality of product
Details of users, specifically login details which could be personally identifying, are separated from demographic information about the user and their result data. Therefore, in the event that a study participant requests that they be removed from the program along with all identifying details, they can be removed from the database while retaining their studies data as anonymous participants, protecting their privacy.
Furthermore, in order to ensure that user data is not proliferated, only the creator of a study is able to access a study and modify its details, and more importantly retrieve result and demographic data about participants in that study. Other researchers are unable to access other studies, which if made possible may be a breach of privacy as participants may have only provided permission to results to the owning researcher. For administrative purposes, any user with administrator rights will also be able to access all studies and their data, as representatives of the Refokus system.
In order to provide scalability and flexibility to researcher created studies, creation of a study can include the creation of an unlimited number of text or slider based questions for post-session and periodic beeper surveys. This gives researchers the ability to customize their surveys to a large extent and it potentially accommodates any possible data points the researcher may wish to collect through survey data.
Furthermore, updating of survey questions or session-specific podcasts is possible while the study is active where there are existing users with partial progress. Completed sessions that receive updates will not be repeated for participants, but any sessions they have not yet completed will be updated to the latest attributes set by the researcher. Any data collected will reflect the survey results according to the version completed by the participant, and so no data is lost either from the old or new version of the study.
In order to improve availability of service, users will be able to download the podcast for their next session ahead of time, even if they are not yet able to start the session due to the imposed daily limit. In the process the mobile app will also update its survey questions to be used for any subsequent post-session survey or beeper surveys. Sessions can be carried out without internet availability, and the result data stored after the session until internet connectivity is restored.
|Project Management||Minutes (Sponsor,Supervisor, Team)||Minutes|
|Metrics||Schedule, Bug, Change Management Metrics|
|Requirements Gathering||Design Documents||Scenario,Storyboard,Navigation Diagram,Prototype|
|Market Research||Market Research|
|Analysis||Use case||Participant & Researcher Use Cases|
|System Sequence Diagram||System Sequence Diagram (web, mobile)|
|Business Process Diagram||Business Process Diagram (As-Is, To-Be)|
|Logical Diagram||Logical Diagram(web & mobile)|
|Testing||User Testing||User Test Results|
|Test Plans||Test Cases|
|Handover||Manuals||User tutorial, Developer Manual, Setup Manual (Contains sensitive information, passed to sponsor directly)|
|Codes||Livelabs server, source code (Contains sensitive information, passed to sponsor directly)|
We have deployed our mobile application on the Google PlayStore:
|Alpha Version||Instructions to download|
|Beta Version||Instructions to download|
|Production Version||ReFokus is on PlayStore now!|
We have deployed our web application on the Livelabs Servers:
|ReFokus on Test Server|
|ReFokus on Production Server|
We have also deployed our web application to the Livelabs Web Server (Hestia), ReFokus Web Application
Number of User Tests: 5
Our testers consist of users with research backgrounds, specifically research assistants currently pursuing their PhD in Psychology. With their experience, we were able to gain valuable feedback with regards to the creation of studies.
Our testers also include SIS Students. With their knowledge and a higher expectation in usability, their valuable feedback helped us improve on our app's usability
For more information about the user tests and the detailed results, please visit the link below:
For each iteration, we have functional test cases to test individual functions. Towards the end of the iteration, we will do regression testing and go through the entire flow of the project to ensure all parts are working.
For the detailed test cases, please visit the link below:
For our bug metrics score, we can see that iteration 5 had an exceptionally high score. This was due to the aftermath of User Test 2 and 3, which proved to be useful for us with the functional and UI bugs spotted. Even though the bug score was well above the threshold level of 10, we managed to solve all the bugs in the scheduled debugging time.
For the detailed bug reports, please visit the link below:
Compile common lessons and reflection for the team and for each team member. Be brief.
Key lessons learned – indicating where the team improved, or would do things differently next time. You may refer to the learning outcome summary in your proposal. A very short checklist style will suffice. It would be very convincing if the knowledge is share at the wiki knowledge base and linked here.
Describe in a paragraph, the key areas of learning or improvement. These should be personal areas of growth or learning. Each individual should list his/her effort, responsibility, actual contributions and personal reflection. Do not repeat team project contributions or member roles. Link if necessary.
"Interest in mindfulness meditation is growing day by day as people seek ways to deal with stress, be more productive, or just be more aware in their everyday life. There are already a lot of apps available to teach mindfulness practices or aid in meditation. However, none of these apps evaluate the effectiveness of the exercises they promote. The ReFokus system will change this. Researchers can now design mindfulness-based interventions that are delivered by an Android app, design survey questions that are then administered to users right after each exercise, and study these effects in a worldwide sample. Users are able to learn and practice mindfulness meditation in the comfort of their own home and at a pace that suits their schedule. The entire interface is easy for researchers and lay people to use, and the data collected are not only helpful to researchers--they are also shared with users as feedback on their own experience with the app. In this way, ReFokus bridges research and practice in the study of everyday mindfulness.
Thanks all for your hard work!" -- Sponsor, Asst. Prof. William Tov