Sprint 1 - Week 02/08/2026 - 05/09/2026

Description of the problem,the proposed solution, the revenue model and the value proposal

• Problem: During this first sprint, we identified that a big problem for university students is that they frequently waste time determining how to use their free periods—specifically deciding who to socialize with and where to eat on campus. Ultimately, the core challenge lies in effectively managing these schedule gaps to maximize their time.

• Solution: Our proposed solution enables users to view the schedule availability of select friends or colleagues, making it easy to coordinate shared free time. It also features a curated activity catalog tailored to the group's preferences, alongside a discovery tool for nearby restaurants that offers perks such as takeout ordering and exclusive discount vouchers.

• Renvenue model: Our app’s primary revenue stream would come from a commission (approximately 5% to 10%) on each to-go order processed through the platform paid by campus restaurants. This is the most robust source because it relates to the product's most frequent and measurable transaction, and the model is already proven by similar apps like Rappi or Uber Eats. Other potential sources include an institutional partnership with the university where a licensing fee is paid to use the app as the official channel for promoting campus activities and events as well as a model where restaurants or brands pay for priority placement in the catalog, or brands and well funded groups sponsor specific cultural or sporting events.

• Value proposal: University students using our app want to make the most of gaps in their schedules whether to grab a bite, hang out with friends, or engage in an activity. Currently, this goal is often thwarted: they lack information on nearby options and the time required for each; coordinating schedules via WhatsApp with multiple people is slow and wastes precious free time; and waiting in line for food eats up even more of their limited break. What they want is simply to use that time effectively, discover new activities and dining spots including deals and promotions tailored to their preferences and coordinate more easily with their friends. We solve this with a shared calendar that automatically cross-references the user's schedule with their friends'; a catalog of activities and restaurants filterable by key criteria, with relevant ads and offers from local businesses seamlessly woven in; and to-go orders that can be placed in advance for ready-to-pickup service. This eliminates the uncertainty of not knowing what to do, replaces manual coordination with automatic schedule matching, and resolves dining hassles while adding value through curated recommendations and exclusive promotions. Ultimately, it helps students make the most of every schedule gap by showing them in seconds what to do, where to eat, and who to join, all without wasting time on coordination or waiting in lines while local businesses gain a direct channel to reach students exactly when they're most receptive.

Empathy maps

Empathy Map 1 - Zair (By Juan Sebastián Ávila Nivia)

Zair's empathy map represents a student with short and changing gaps between classes who wants to make the most of his limited free time. He tries to balance academic, work, going to the gym, and spending time with friends, but coordinating with others is difficult because their schedules do not always match. This makes him feel pressure and sometimes unsure about what activity is worth doing during each gap. His behavior changes depending on how much time he has available.

Empathy Map 2 - Juan Jose (By Tomas Hernandez)

Juan Jose's empathy map focuses mainly on the difficult of deciding where to eat during gaps between classes. He wants to discover more food options, but considers factors such as available tables, distance, price, and the amount of free tim he has. He often discovers restaurants through experience, recommendations, or luck and prefers not to leave the university when his gap is short. This can make eating between classes frustrating and uncertain.

Empathy Map 3 - Paula (By Martín Leschhorn)

Paula's empathy map represents a student who tries to use her gaps productively while keeping her plans flexible. Academic work is usually a priority, so she often uses free periods to complete assignments, although she may also eat, meet friends, or do sports when enough time is available. Her workload can change unexpectedly, which makes planning activities difficult. She feels satisfied when she manages to use a gap efficiently instead of wasting it.

Empathy Map 4 - Mateo Vargas (By Sebastian Vargas )

Mateo's empathy map shows a student who is especially interested in social activities, sports, and affordable food options during his free periods. He feels that the university has limited food variety and often considers options outside campus, although distance and price can make them incovenient. He also values spending his gaps with friends and would benefit from knowing when they are available. His free time is generally used for socializing or sports rather than academic work.

Empathy Map 5 - Santiago Bernal (By Alejandra Sanabria)

Santiago's empathy map shows a student who is a student focused on his degree and thesis, while trying to better manage his time and workload. He feels academic pressure, frustration, and isolation, but finds balance through exercise, video games, and time with his girlfriend. His routine revolves around classes, thesis work, and occasionally studying in the library before going home.

Personas

Persona 1:

Juan Hernschhorn is a 20–21-year-old Engineering student at Universidad de los Andes. He has a fragmented and constantly changing academic schedule, which means he often has to decide what to do with the limited time between classes. His smartphone is his main way of communication, organization and search of information. He wants to make better use of his time on campus but lacks clear information abaout his available time, activities, and food options, which often leads to last minute decisions.

Persona 2:

Jhayzon is a 20–23-year-old university student, he cares a lot on his academic responsabilities and often uses the time between clases to complete assignments or study. Even though he values excercise, rest and his personal well being, when the workload increases, this are usually the first to be sacrificed. He relies upon his smartphone, laptop and other university platforms to stay organized and manage his academic experience, thus making a challenge finding a balance between keeping up with his studies and making time for his other activites, like spending time with Friends.

Analitycs persona

Description: Daniel Duplat is a 20–25-year-old single Data Analyst and Engineering student at Universidad de los Andes. High tech-savvy and quick to adapt to new applications, he relies primarily on his Android 16 smartphone and work laptop to perform his daily work. In his role, Daniel wants to analyze what students do in their free time and understand their usage patterns across different time gaps. He seeks to identify student location and activity preferences to develop features tailored to their actual routines and available time, making personalized offerings possible. However, he faces significant obstacles: student data is disorganized and outdated, making manual collection slow, hard to scale, and ineffective for tracking behavior changes. Furthermore, comparing activities across varying schedule gaps makes identifying common free-time patterns particularly difficult.

PA's

PAS 1 — Knowing what to do during a gap

Problem: Students have gaps between classes and sometimes do not know how to use that time in a useful or enjoyable way.

Alternative: They normally improvise by studying, sitting somewhere, eating, or messaging friends to see if anyone is free.

Solution: An app that detects the length of the gap and recommends activities that can realistically be completed before the next class.

PAS 2 - Coordinating with friends

Problem: Students want to spend their free periods with friends, but their schedules often do not match.

Alternative: They message friends individually or ask in group chats until they find someone available.

Solution: A shared availability system that automatically shows which friends have overlapping free time.

PAS 3 - Finding food that fits the available time.

Problem: Students may want to eat during a gap but do not know which option fits their remaining time, location, and budget.

Alternative: They go to familiar restaurants or walk around until they find something sutiable.

Solution: Recommend food options based on the student's available time, distance, price, and preferences.

PAS 4 - Discovering new food options

Problem: Students do not know all the restaurants and affordable food options available around campus.

Alternative: They discover new places through friends, by walking past them, or simply by chance.

Solution: A centralized food catalog with nearby restaurants, prices, location, food type and student information/reviews.

PAS 5 - Arriving at a full restaurant.

Problem: Students can spend part of a short gap walking to a restaurant only to find that there are no tables or the waiting time is too long.

Alternative: They search for another restaurant or return to a familiar cafeteria after already losing time.

Solution: Show estimated occupancy, waiting time, or current availability before the student decides where to go.

PAS 6 - Finding campus activities

Problem: Students may want to exercise, play sports, or participate in another campus activity during their gaps but do not know what is available at that moment.

Alternative: They use what they already know, check different university platforms, or simply the activity.

Solution: A centralized activity catalog showing available activities, facilities, schedules, and reservation links.

PAS 7 - Academic work unexpectedly consumes the gap.

Problem: Students cannot always plan their free time because assignments and academic responsibilities can suddenly become more important.

Alternative: They cancel their original plan and use the entire gap for academic work.

Solution: Provide flexible recommendations that can quickly adapt to a shorter or changed free-time window.

PAS 8 - Organizing a spontaneous plan

Problem: Even when students know what they want to do and who is free, coordinating the plan takes time.

Alternative: They create several WhatsApp messages to decide the activity, place, time, and participants.

Solution: Let a user create a plan inside the app and send one invitation containing the activity, location and time.

PAS 9 - Having nobody familiar available.

Problem: A student may have a long gap and want to socialize or do an activity, but none of their usual friends are free.

Alternative: They spend the gap alone, study, or abandon the activity, they wanted to do.

Solution: Suggest other university students with compatible schedules and shared interests who are interested in the same activity.

PAS 10 - Information is fragmented

Problem: Students need to check several places to find schedules, activities, food, events, reservations, and friends' availability.

Alternative: They switch between university platforms, calendars, maps, social media, WhatsApp, and websites until they find what they need.

Solution: A single app that combines that student's available time with relevant activities, food options, events, and social plans.

Context Canva

ContextCanva.drawio.html

Business questions

Type 1 questions

• Is the average loading time of the app less than 1 second?
• Which screen or app component has the highest crash rate?

Type 2 questions

• How much time do students spend from opening the app to selecting an activity for their free period?
• What is the proportion of recommended activities that are selected by the students during their available free time windows?
• How often do recommended activities match the duration of the students available free time?
• Which of the recomended categories is most frequently selected during the different free time durations?

Type 3 questions

• Which feature is used by less than 40% of the active users?
• What percentage of active users use the Friend Availability feature to create or join a plan?
• How does the use of the Friend Availability feature affect the number of plans created with other students?
• How does removing the Friend Availability feature affect the number of social plans created by users?

Type 4 questions

• Which restaurants and activity providers represent the strongest partnership opportunities based and students' recommendation views and selections during their free periods?
• Which activities or restaurants have the highest demand during specific time periods, and which of these patterns could be monetized through partnerships or targeted promotions?

Type 5 questions

• How does network quality affect the loading time of recommendations and the rate at which students select an activity?
• Which combination of student preferences, free-time duration, location, and friend availability produces the highest rate of successful plan creation?

VD MAP

Mejor visualización del VD MAP

Scenarios

Functional scenarios

1. Juan, a 6th semester engineering student at Universidad de los Andes, has a 40 minute gap between two classes and wants to grab lunch with three friends but their schedules almost never line up, and coordinating by text usually falls apart. He opens the app's shared availability view for his friend group and instantly sees that all four of them are free during that same window today. Instead of guessing or waiting for replies, he taps "propose this gap" and the group confirms in minutes, turning what used to be a source of stress into a two-tap decision.
2. Between two back-to-back engineering courses, Juan unexpectedly ends up with a 25 minute gap because a class was cancelled. Rather than spending it deciding whether to eat, rest, or check his phone aimlessly, he opens the app and it surfaces quick suggestions sized to exactly 25 minutes a nearby café with current table availability and a short walk to grab something to go. He picks the café, sees it has open tables right now, and avoids the indecision that usually eats into his short breaks.
3. Juan heads to the central cafeteria between classes expecting to eat, but on a normal day he'd have no way of knowing if it's full until he's standing in a crowded line often forcing him to go backtrack and settle for whatever alternative is nearby. This time, he checks the app first and sees the cafeteria is showing no available tables at this hour. Instead of walking over blind, he browses nearby options with live table status, finds a spot with room, and orders takeout ahead of time so it's ready when he arrives.
4. Juan has a two-hour gap between classes twice a week and knows he should use it productively for the gym, an assignment, or catching up with friends, but usually ends up scrolling his phone, undecided. He opens the app, filters the activity catalog by "fits 2 hours" and "on campus," and sees the gym listed with current availability. Seeing a concrete, time-matched option removes the friction of deciding, and he heads straight there instead of losing the gap to indecision.
5. Jhayzon, a final semester engineering student, has a 50 minute gap before his next class and needs to know whether that's enough time to make progress on a pending assignment or whether he should use it differently. He opens the app and filters the activity catalog by task type and duration; it surfaces "quick assignment review" alongside "short walk" as options that realistically fit 50 minutes. Seeing his time framed this way helps him commit to a plan instead of second guessing whether he's "wasting" the gap.
6. Jhayzon wants to keep exercising regularly, but he admits that workouts are usually the first thing he cancels when his workload spikes, since he never has a clear window that matches how much free time he has. One afternoon he has exactly 35 minutes free before his next class. He opens the app's activity catalog, filters for "exercise" and "35 minutes or less," and finds a short on-campus workout circuit that fits precisely. Because the suggestion matches his real available time instead of a generic hour-long class, he follows through instead of cancelling.
7. Jhayzon has unfinished coursework and normally feels uncomfortable stepping away from it, even for a few minutes, which means rest keeps getting pushed aside. During a short 15 minute gap, the app suggests a nearby quiet spot for a quick break rather than another study block, framed explicitly as fitting his available time rather than open ended free time. Seeing the break sized to a specific, small window not an open invitation to slack off makes it easier for him to step away without feeling like he's neglecting his work.
8. Jhayzon coordinates with two classmates for a study session before an exam, but their workloads change day to day, so setting a plan rarely holds up. On the morning of, he opens the shared availability view and sees a 90 minute window where all three are currently free, something that wasn't true the day before. He then filters the activity catalog for "quiet study space" and picks a library nook nearby, turning a plan that usually falls apart into something locked in same day.
9. Daniel, a data analyst supporting the platform, needs to understand how students like Juan and Jhayzon use their free time so the team can personalize activity and restaurant offers, but manually gathering this from surveys is slow and the data goes stable fast. He opens the internal analytics dashboard, which aggregates anonymized gap durations and activity choices logged directly through the app. He notices that most engineering students in mid semester have gaps under 30 minutes concentrated around midday, a pattern he couldn't have reliably identified from outdated, manually collected data.
10. A few weeks into the semester, Daniel notices in the dashboard that more students are choosing short exercise activities during small gaps instead of only food related suggestions, a shift that wouldn't have shown up in the team's last manual survey, done a month earlier, because the app captures this behavior automatically and continuously, Daniel can flag the trend to the product team right away and recommend expanding the short-workout options in the activity catalog, instead of waiting for the next slow data collection cycle to catch up.

Quality scenarios

Scenario name	Quality attributes	App status and context	Changes in context	System reaction
1. Connection loss during calendar	Eventual connectivity, resilience	The app is syncing recent changes to the shared calendar with the server	The student walks into a basement classroom with no signal	The app saves changes locally, shows a "pending sync" icon, and retries automatically once connection is restored
2. High order concurrency at peak lunch hour	Scalability, performance	Hundreds of students try to place pre-orders between 11:45 and 12:00	Request traffic suddenly spikes 10x	The system load-balances across servers, queues orders, and keeps response times under 3 seconds without losing any order
3. Screen reader navigation in the catalog	Accessibility, usability	A visually impaired student opens the catalog with TalkBack active, during a 20-minute gap	He tries to filter by "fast food" using reader commands	All elements have descriptive labels and a logical navigation order, letting her complete the filter without seeing the screen
4. Low screen visibility due to ambient light	Usability, interface adaptability	A student checks his order pickup time on a sunny terrace at noon	Ambient brightness is very high, making the normal contrast unreadable	The app detects the light sensor (or the user enables high-contrast mode) and automatically adjusts the color scheme
5. Cross-restaurant request tampering	Security	A restaurant's panel is open, managing its incoming orders	An actor tampers with the request, changing the ID to access another restaurant's orders	The backend validates that the session token belongs to the resource's owner, rejects the request (403), and logs the attempt
6. Main server failure during peak demand	Availability, resilience	Hundreds of students are browsing catalogs and the calendar simultaneously	The main server fails unexpectedly	The system fails over to a replica server, keeping the outage under 5 seconds
7. Exchange student with phone set to English	Internationalization	An exchange student opens the app for the first time	The phone's OS language is set to English	The app detects the device language and displays the entire interface, catalogs, and notifications in English (with an option to change it manually)
8. Switching from Wi-Fi to mobile data	Eventual connectivity, GUI responsiveness	The restaurant catalog is loading as the student walks out of the building	The network switches from Wi-Fi to mobile data with a brief disconnection	The app keeps the session active, shows a discreet loading indicator, and retries the request without losing screen state
9. Unauthorized access to a classmate's calendar	Security, privacy	A student looks up a classmate's profile from the shared calendar	He requests to view a detailed schedule that hasn't been shared with him	The app hides the private information and only shows general "busy/free" status until the classmate grants full access
10. Last-minute order cancellation	Resilience, data consistency	An order is in "in preparation" status at the restaurant	The student cancels the order right as the restaurant is about to mark it ready	The system resolves the conflict by prioritizing the most recent update, notifies the restaurant in real time, and issues an automatic refund or credit

Ethics Video

As GitHub has a strict policy when uploading files larger than 10mb to a wiki page, we decided to upload the video to YouTube to allow the examinators to review the video easily. However, we will also provide a download link to prove this video wasn't modified after the deadline of the Sprint 1 deliverable.

• See Ethics Video in YouTube
• Download Video