Im

Improved Comprehension using ChatGPT and Active Recall AI

Hacker News

Improved Comprehension using ChatGPT and Active Recall AI

Yes, this is another ChatGPT application. No, this post wasn’t written using ChatGPT as you will soon find out after stumbling through my mediocre writing style. I built a new education-focused ChatGPT-based tool called Active Recall AI. Active Recall AI aims to help students who struggle with reading comprehension or just learning in general. It is something that I personally struggle with as well as my daughter. I was never a strong academic and it took me a long time to figure out “how I learn” most effectively. It wasn’t until I became a teacher that I discovered that I am one of those people that learn best by not only doing but also by teaching. I have spent hundreds of hours at the podium teaching technical topics to hundreds of students. I felt like I really unlocked my “learning super power” by standing at that podium and articulating every minor detail of the topic we were studying. You see, I am the kind of person who, when reading, only really absorbs a miniscule amount of the content I am reading. Reading is really just a miserable experience for me because I just kind of drift off. It is not until I try to articulate the topic to others that I begin to truly understand the subject matter. Enter Active Recall AI. Active Recall AI is a tool I built that aims to fill that gap for those who have a similar learning style. Active recall learning is nothing new and it is quite well studied. If you are not familiar with what active recall learning is then let me explain it to you. I think most students are guilty of cramming for a test last minute by simply re-reading all their lecture notes. This works to some extent but it focuses too much on putting information into your brain as opposed to actually pulling it out. With active recall learning techniques, instead of re-reading your notes ad nauseam and praying for a miracle, you instead spend most of your time studying by articulating either through voice or written word your understanding of a subject. It’s kind of like Rubber Duck Debugging where you talk to your rubber duck about the software bug you are working on and BAM!, you have an epiphany and remember that small mistake you made. Re-reading your code over and over again isn’t what solved the problem, it’s the act of speaking your problem out loud and pulling that information out of your brain that solved the problem. Active Recall AI is basically your tutor or learning buddy that never sleeps and is always ready to listen to you. Simply write a written statement on the uploaded learning material and Active Recall AI will assess and grade you on your understanding of the subject matter. Although Active Recall AI is in the early stages of development, it can be an incredible learning tool to help you reach your academic goals. My goal is to extend upon the MVP I built to include additional features like automatic quiz generation, prompt recommendations that target your weakest areas and a socratic bot to dialog with. It has been an incredibly fun project so far and is my first dip into integrating ChatGPT into my own software. I hope you enjoy using it as much as I enjoyed making it. Visit https://www.activerecallai.com to try it out yourself.

Share card

Actual performance

1points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: new, chatgpt, using · Missing: mac, agents, macos
91%91% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Missing: supports, reddit linkedin, podcasting
78%78% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
TrustMRRLess likely to generate early MRR · Strong signals: personal, way, education · Missing: mobile apps, ios, entrepreneurs
48%48% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: soon · Missing: plus, platform, intuitive
46%46% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Hacker NewsMay not resonate with HN audience · Strong signals: io · Missing: https docs, excited, just released
38%38% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
Acquire.comPre-revenue stage for this audience · Strong signals: active · Missing: arr, mrr, revenue
14%14% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Strong signals: chat · Missing: web3, crypto, cryptocurrency
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Correct prediction on native model

Similar products

Mindcup
Mindcup62%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Active recall notes workspace with FSRS spaced repetition

Indie Hackers1education
Sk
SkillPress – Learn JavaScript via spaced repetition and active recall52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

SkillPress – Learn JavaScript via spaced repetition and active recall

Hacker News64
Mi
Mithril Improved with AI32%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Mithril Improved with AI

Hacker News1
Find By
Find By

Craigslist improved with geolocation

BetaList
Im
Improved rails strong_parameter implementation41%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Improved rails strong_parameter implementation

Hacker News2
Ac
Active circles43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Active circles

Hacker News1
HEIJI Active
HEIJI Active54%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Activewear Wanita

Indie Hackers1$560/moclothing
YA
YAML to Django Using ChatGPT49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

YAML to Django Using ChatGPT

Hacker News4
AI
AI-tool using WebRTC for improved and respectful conversations49%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AI-tool using WebRTC for improved and respectful conversations

Hacker News1
Capillary.io
Capillary.io26%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Nailfold capillaroscopy improved with AI

Indie Hackers1ai