Language App

Exploring the creation and use of a hyper-editable, personal repository of words, expressions, and additional communicative methods as a means to learn. Includes research, prototypes, and plot twist.

Background

I have long held interests in communication methods, cultures, linguistics, and most relevant: languages. The exposure to a wide variety of these growing up was not only a privilege, but it allowed scattered and - unfortunately - ephemeral acquisition of the knowledge shared. I wanted a tool to help me remember these experiences for good, whether on my own or as a log to reference and refresh memory.

90 days

Timeline

My Role

Lead Researcher & Designer

Initial Problem

I want a way to store and access words and phrases from other languages. Initial market research showed no suitable product.

Goal

To create a living directory of learned language that allows for quick archival and retrieval.

Approach

I created a simple workflow of what immediate actions would be needed based on the scenario of being in a conversation with friend.

Great! But what inspired these requirements? I didn’t outline any first, which is a mistake leading to early ideation of features I would like to see (for myself) in the product.

I corrected by setting these aside to focus on the users, the problem, and defining the initial product to provide feedback to begin the work.

Users

Individual engaging in foreign language with native speaker or media passively
Individual with varied interests, learning new language, and interacting with native speaker or media intentionally
Individual actively seeking foreign language study and engagements with native speaker or media

Product Defined

Digital tool to assist in language acquisition and practical conversation when interacting with native speakers and consumed media.

Minimum Requirements

Record word(s) and phrase(s) with definition
Be able to record quickly

Nice to Have

Ability to look up words through categories

Research

Preparation

With initial market research and a competitive analysis, there was some aid in narrowing down what ways users may have come across learning language in an intentional space or through tool usage.

I researched different learning types for further understanding the breadth of information I should be capturing in the interviews.

This includes talking with primary school teachers, language tutors, and school counselors.

Learning Types Resources

VARK Research - Distribution of Learning Preferences. 2023, vark-learn.com/research-statistics/.

Khan, Ameer Hami Ad , et al. “Evidence-Based Approaches to Learning.” Advances in Medical Education and Practice, 2018, pmc.ncbi.nlm.nih.gov/articles/PMC6101737/pdf/amep-9-581.pdf.

Hussain, Imran. (2017). “Pedagogical Implications of VARK Model of Learning.” Journal of Literature, Languages and Linguistics, 2017, researchgate.net/publication/337274707_Pedagogical_Implications_of_VARK_Model_of_Learning.

Script

I defined the initial scope of the script and goal of the interviews. It is simple, open-ended, and styled to allow for a fluid conversation where information can be collected without the structure disrupting.

You can view the outline of original script on Notion here.

The script was broken into 6 general sections:

Understanding the user’s language background and any additional context
Understanding how the user learns
Giving a scenario and asking what the user’s approach would look like or to respond generally to the scenario
Additional prompts: exploring (with scenarios as ready references) in specifics their approach to retaining the information
Further investigation of discussed items, motivations, and pain points

Interviews

I selected individuals to interview based on the 3 criteria previously outlined. Interviews were recorded with consent, consisting largely of in-person with remote interviews supplementing. Interviewed individuals will return for user testing.

Initial Round

I interviewed 5 individuals to start. When I began to synthesize the information, it wasn’t long to start seeing the scope broadening and a flaw appearing.

Starting with a small batch of interviews was incredibly helpful in understanding how information heavy & diverse this project would become, while also highlighting a major problem to be corrected with proceeding interviews.

Immediate Insights

Big range of learning types

Habits in learning looks to be key to understanding
Need a wider pool of individuals
- with important attention to first insight

Looking at the Data

The glaring omission in the initial interviews was an absence of monolingual speakers.

Not only that, but every individual interviewed initially grew up learning an additional language concurrently with what they considered to be their native language (attributed to primary language spoken in household).

Additional Rounds

To correct, I selected and interviewed:

users who learned/are learning an additional language at a late age
users who come from monolingual households
users whose additional languages vary more greatly in language family connections

IMAGE: Interviews recorded into categories in cards. This mockup is for illustrative purposes only and is intentionally kept simple. More than 5 individuals were recorded.

Synthesizing the Data

Combing through and understanding all this data was cumbersome, and it ultimately was digested into 4 layers, with a bonus for additional testing and ideation.

Interview Collection

i

Let’s understand the initial recording and organizing of information from the scripted interviews first before we break it down.

All the information and takeaways were organized to the following categories and into cards.

INTRODUCTION

Basic information more inline with what is expected from a user persona, ex. age, occupation, nationality, education, etc.

LANGUAGES

Languages spoken with proficiency, attempt, and family history/ties noted; language family and grouping also recorded

GEOGRAPHIC BACKGROUND

Basic geographic information on background, including work history and any time living away from home (family included) when relevant

LEARNING

What learning types have been historically helpful plus notes about experiences learning language or new things

FURTHER INVESTIGATION

Typically a follow-up on the learning section, zeroing in more on the emotional side or investigating decisions

SCENARIOS

Any relevant responses or connections to scenarios, including quotes

WHAT MOTIVATES YOU?

Understanding choices and responses with deeper investigation. Includes quotes and direct ties to language relationships and education

Breakdown of Cards – Overview

1a

The green section grouped together above is higher level information for great initial context and with extra data for deeper investigation at a later stage, but primarily sticking to the scope of the interviews and the goals, I broke the remaining categories into insights and pain points.

By combining all the cards together, it provided a overview of the dataset.

Learning Insights

Individuals showed little success relating fruitfully, but there is plenty of data about learning productivity. Plus many notes on tool.

Learning Paint Points

Individuals reported struggle learning with motivation and relating information, and there were many notes on tools.

Breakdown of Cards – Analyzing

1b

Patterns began to reveal themselves, and I grouped them accordingly (seen below in like-colors) for further analysis.

Identifying Patterns

2

The 4 predominant commonalities were defined and grouped under the following banners.

Please note: no mockup provided here for this step, but follows the same visual and organization as the other cards, but with each header being one of the below and the cards being white.

Ways identified how individual learns, plus what is or isn’t helpful when learning. Example: reading and writing is helpful, but speaking is not.

Mechanics

Falls under Mechanics, but is supplemental to traditional learning with helpful tactics.
Example: writing down notes in phone.

Tools

Falls under Mechanics, but a way to more deeply understand language presentation that is relevant to the individual’s learning.
Example: needs to see context of use with words or phrases.

Relating

Factors that push towards or away from the individual learning.
Example: I want to learn a second language to travel to that city alone.

Motivations

Further Investigation

3

Like previously (1b), I analyzed the cards grouped under the categories for further investigation. The cards within the categories (detailed above) were broken into sets of 3-4 each for deeper understanding.

Here is how I investigated each and defined where the data best fits within.

1. Mechanics – 2. Tools – 3. Relating – 4. Motivations
1. Mechanics – 2. Tools – 3. Relating – 4. Motivations
1. Mechanics – 2. Tools – 3. Relating – 4. Motivations
1. Mechanics – 2. Tools – 3. Relating – 4. Motivations

Final Breakdown

4

I have learned so much at this point and understand where to go next.

Mechanics provided great insights already, but I wanted to spend more time to better understand the connections.

I marked overlap and then visualized this in a Venn Diagram to identify the similarities and relationships.

IMAGE: (above) Mockup demonstrates revisiting this data to discover overlaps, seen in the color scheme of the highlighted cards.

IMAGE: (above) Mockup of Venn Diagram showcasing a more easily identifiable relationship within Mechanics.

Takeaways

Interviews provided an immense amount of information regarding how the individuals did or did not learn
Diagram to left shows the interconnected relationship of experiences when learning
Diagram highlights the high level of attention required of Mechanics in the user journey
- Product features will have a close, highly impactful relationship here

Putting It Together

With the benefit of a clear, simple goal and minimum requirements, along with competitive analysis of products relating to language and archiving, it is clear that this product can use existing patterns and rely on expected features. It is how the features are accessed that calls focus.

Because of the impact of features and an established design philosophy thanks to what I’ve learned from the interviews, synthesis, and research, attention now turns to light feature mapping. In the background, I am also collating and playing with task flow and how the larger system interacts with the features.

Features

24 features have been identified to be included and tested.

Features x Learning Types

In architecting the larger system, I wanted to see

how well do these features support different learning types
what is the general coverage of learning types supported

This was created based upon research and further tested by reaching out through different teachers.

Features x Accessibility

Continuing with architecting the system and weighing prioritization with succeeding in the product’s primary goal,

I wanted to see how well each feature is supporting how a user may learn
I wanted to see where gaps exist
I wanted to anticipate pain points

The scale of help-to-hurt began on my own research and validated through working with education professionals.