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A customizable homeschool curriculum based on great books

Hacker News

A customizable homeschool curriculum based on great books

Assembling an educational curriculum for your homeschooled child is way more work than it needs to be. Comprehensive prepackaged curricula often cost thousands of dollars, are boring and don’t provide much in the way of customization. Video-based online courses aren’t academically rigorous and require kids to spend too much time in front of a screen. Great Books Homeschool aims to solve that with an editable K-8 curriculum compiled from the best books and activities for each subject. The curriculum is fully customizable, so you can move the material to different places in the schedule, remove items or add your own. Academic records are automatically created (no more ring binders). For the past decade I’ve been seeking out and testing the best and most enjoyable learning resources for each subject while homeschooling my two kids. This project aims to share the fruit of that effort with other homeschooling families. I'd welcome feedback!

Visit product View on Hacker NewsNov 19, 2022

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Indie HackersFits the IH revenue-focused audience · Strong signals: created · Missing: supports, reddit linkedin, podcasting

88%88% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Hacker NewsStrong engagement from HN community · Strong signals: ide, io · Missing: https docs, excited, just released

62%62% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

Product HuntOn track for Day 1 leaderboard · Missing: mac, agents, macos

57%57% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

TrustMRRFits verified-revenue profile · Strong signals: video, way, education · Missing: mobile apps, ios, personal

52%52% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Missing: plus, platform, intuitive

44%44% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

17%17% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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