[{"_1":2,"_315":-5,"_316":-5},"loaderData",{"_3":4,"_91":92,"_251":252,"_314":-5},"root",{"_5":6,"_32":33,"_58":59,"_89":90},"ctx",{"_7":8,"_18":19,"_20":-5,"_21":22,"_23":24,"_25":26,"_27":26,"_28":29,"_30":31},"auth",{"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5},"sessionClaims","sessionId","userId","actor","orgId","orgRole","orgSlug","orgPermissions","factorVerificationAge","environmentVariableKeys",[],"user","preferences_keybindings","default","preferences_theme","light","preferences_fixers",false,"preferences_copilot","preferences_model","claude-3-5-haiku-20241022","notification_count",0,"ENV",{"_34":35,"_36":37,"_38":39,"_40":41,"_42":43,"_44":45,"_46":47,"_48":49,"_50":51,"_52":53,"_54":55,"_56":57},"REACT_APP_SENTRY_DSN","https://586020d86f05489db63a554690acf1e9@o1398359.ingest.sentry.io/6724499","VAL_RUNTIME_NAME","prod","RENDER_GIT_COMMIT","fa80b67e1f763bfb4b247c3f5ca4f0b0730f3f5c","RENDER_GIT_BRANCH","main","CLERK_PUBLISHABLE_KEY","pk_live_Y2xlcmsudmFsLnRvd24k","POSTHOG_API_TOKEN","phc_nmoyuAkStEZuUp69rYlg1DZgrIt19Gx0Y4Hwf8tGgJP","POSTHOG_API_HOST","https://wart.val.town","WEB_API_TEMPLATE","https://{val}.web.val.run","APP_URL","https://www.val.town","MODULE_URL","https://esm.town","API_URL","https://api.val.town","WORKER_FINGERPRINT","799d99f2805306c2714a7cfefbeae178","clerkState",{"_60":61},"__internal_clerk_state",{"_62":63,"_64":43,"_65":66,"_67":66,"_68":26,"_69":66,"_70":66,"_71":66,"_72":66,"_73":66,"_74":66,"_75":66,"_76":66,"_77":78,"_87":26,"_88":26},"__clerk_ssr_state",{"_9":-5,"_10":-5,"_11":-5,"_12":-5,"_13":-5,"_14":-5,"_15":-5,"_16":-5,"_17":-5},"__publishableKey","__proxyUrl","","__domain","__isSatellite","__signInUrl","__signUpUrl","__afterSignInUrl","__afterSignUpUrl","__signInForceRedirectUrl","__signUpForceRedirectUrl","__signInFallbackRedirectUrl","__signUpFallbackRedirectUrl","__clerk_debug",{"_79":26,"_80":66,"_81":82,"_83":66,"_84":43,"_85":26,"_86":66},"isSignedIn","proxyUrl","reason","session-token-and-uat-missing","message","publishableKey","isSatellite","domain","__telemetryDisabled","__telemetryDebug","remixVersion",2,"routes/_app.v.$handle.$name",{"_93":94,"_95":96,"_94":97,"_246":-5,"_247":-5,"_248":249,"_130":131,"_138":139,"_100":101,"_98":99,"_118":-7,"_50":51,"_250":26},"type","val","author","6906d0a1-0165-46b9-8717-60dfd935316a",{"_98":99,"_95":96,"_100":101,"_102":103,"_104":-5,"_105":106,"_107":-5,"_108":109,"_110":111,"_112":26,"_113":111,"_114":115,"_116":117,"_118":119,"_120":26,"_121":31,"_122":123,"_124":123,"_125":123,"_126":31,"_127":31,"_128":-5,"_20":129,"_134":-5,"_135":-7,"_136":137,"_138":139,"_140":141},"name","spacedRepetition","valNameId","40f56c50-a423-4f53-ac92-4d7a209c6ee7","parentFolderId","c3b01626-9a2b-41d4-be28-8d4787819725","isOwned","privacy","public","readme","valType","script","currentVersion","3f520a06-b7a2-11ee-9d70-325518e2651b","legacyPrivate","id","code","/** @jsxImportSource https://esm.sh/react */\nimport { generateLessonHtml } from \"https://esm.town/v/petermillspaugh/lessonTemplate\";\nimport { renderToString } from \"npm:react-dom/server\";\n\nconst TITLE = \"Spaced repetition\";\n\n// TODO: better prompt?\nconst FILL_BLANK = (\n <>\n What is a forgetting curve?\n \n);\n\nconst CONTENT = (\n <>\n

Spaced retrieval practice

\n \"If learners spread out their study of a topic, returning to it periodically over time, they remember it better.\n Similarly, if they interleave the study of different topics, they learn better if they had studied them one at a\n time in sequence.\"\n

\n The first sentence refers to spaced repetition. The second sentence refers to{\" \"}\n interleaving, which will be covered in more depth in a future lesson.\n

\n\n

Forgetting curves

TODO

\n\n

Flash cards

TODO

\n\n

Automating spaced repetition with Anki

TODO

\n\n

Crystallized versus fluid knowledge

TODO

\n\n

Mental models

\n \"A mental model is a mental representation of some external reality.\" Fitting new knowledge into an existing\n mental model or creating a new mental model that connects to another existing one is key for learning.\n

\n Placing new knowledge in a larger context aids learning. I've termed this contextualization{\" \"}\n so that I have a label to attach to the concept, although that's not an official term. Same idea as fitting new\n learnings into an existing mental model.\n

\n You can fit new knowledge into an existing mental model, and that connection improves retention. Or you might\n create a new mental model that connects to another existing mental model.\n

\"All new learning requires a foundation of prior knowledge.\" Learn the fundamentals!

\n \n \"Learning always builds on a store of prior knowledge. We interpret and remember events by building connections\n to what we already know. Long-term memory capacity is virtually limitless: the more you know, the more possible\n connections you have for adding new knowledge.”\"\n \n

Identifying underlying rules helps solve related but unfamiliar problems later.

\n\n

Why memory is important

\n There's a common refrain that rote memorization is not valuable, except maybe in fields like law and medicine\n where you need to memorize a high volume of information for ready retrieval on the job. Instead, the argument\n goes, we should focus on critical thinking and problem solving. Facts and information are always a quick Google\n search away, anyway.\n

\n Make It Stick{\" \"}\n challenges that idea, building a compelling case that memory is crucial for our reasoning ability.\n

\n \n \"Memory plays a central role in our ability to carry out complex cognitive tasks, such as applying knowledge to\n problems never before encountered and drawing inferences from facts already known.\"\n \n

\n \n);\n\nconst QUIZ = [\n {\n question: \"\",\n answer: \"\",\n },\n];\n\nexport const spacedRepetition = {\n title: TITLE,\n fillBlank: FILL_BLANK,\n quiz: QUIZ,\n fetchHtml: (email: string, lesson: number) =>\n generateLessonHtml({\n email,\n lesson,\n title: `Lesson ${lesson + 1}: ${TITLE}`,\n fillBlank: FILL_BLANK,\n content: CONTENT,\n quiz: QUIZ,\n }),\n};","createdAt",["D",1705761796998],"version",26,"currentUserHasLiked","likeCount","forkCount",1,"referenceCount","dependencyCount","commentCount","prCount","mergedPr",{"_130":131,"_132":133},"handle","petermillspaugh","profileImageUrl","https://images.clerk.dev/oauth_github/img_2TFg9SMWVOcMJQ588IzCEa1VVhI.jpeg","forkedVal","interval","slug","petermillspaugh/spacedRepetition","description","@jsxImportSource https://esm.sh/react","versions",[142,145,149,153,157,161,165,169,173,177,181,185,189,193,197,201,205,209,213,217,221,225,229,233,237,240,243],{"_118":119,"_143":-5,"_116":144,"_113":111},"prId",["D",1705761796998],{"_118":146,"_143":-5,"_116":147,"_113":148},25,["D",1705761041457],"7cfb8c4e-b7a0-11ee-9cc0-325518e2651b",{"_118":150,"_143":-5,"_116":151,"_113":152},24,["D",1705761019917],"7024ccd8-b7a0-11ee-b666-325518e2651b",{"_118":154,"_143":-5,"_116":155,"_113":156},23,["D",1704145995110],"8a5eccb3-2226-47ea-9d1e-ccf219183ee4",{"_118":158,"_143":-5,"_116":159,"_113":160},22,["D",1704145216926],"3d5f75d3-3c62-40bd-8c3c-fb69e6a218a7",{"_118":162,"_143":-5,"_116":163,"_113":164},21,["D",1704145183090],"57cd5b70-bc5a-4564-b445-882a9cac6027",{"_118":166,"_143":-5,"_116":167,"_113":168},20,["D",1704144386878],"d7abce3f-3d7e-4077-a284-6071ab20f93b",{"_118":170,"_143":-5,"_116":171,"_113":172},19,["D",1704143943395],"95bb5d79-6fce-4cfe-a50c-f9a94c230b81",{"_118":174,"_143":-5,"_116":175,"_113":176},18,["D",1704143756166],"680bbfc0-bf88-4d45-b25a-365e5b1b7f80",{"_118":178,"_143":-5,"_116":179,"_113":180},17,["D",1704143706376],"edeea0b1-0242-4862-ad58-eac2344f7dbb",{"_118":182,"_143":-5,"_116":183,"_113":184},16,["D",1704131361185],"d6dc8f80-a65e-4a23-806c-3997b00eb92e",{"_118":186,"_143":-5,"_116":187,"_113":188},15,["D",1704130551439],"587500c9-be85-4afc-9dca-8f474ca39fea",{"_118":190,"_143":-5,"_116":191,"_113":192},14,["D",1704130536561],"34960d81-ebfb-495c-b1cc-d7783d39f99d",{"_118":194,"_143":-5,"_116":195,"_113":196},13,["D",1704072919383],"5179a111-ab0b-4e3a-b426-739d2ec464e2",{"_118":198,"_143":-5,"_116":199,"_113":200},12,["D",1704040298135],"94668c80-5976-4962-9632-a2926a18dd04",{"_118":202,"_143":-5,"_116":203,"_113":204},11,["D",1701645410180],"faa9fcf1-f91c-491b-81df-5a77a742ac5c",{"_118":206,"_143":-5,"_116":207,"_113":208},10,["D",1701645058973],"1d65374f-3457-4050-a4c4-6b2d8cf49582",{"_118":210,"_143":-5,"_116":211,"_113":212},9,["D",1701644915324],"45232937-4873-4f56-8492-412579118780",{"_118":214,"_143":-5,"_116":215,"_113":216},8,["D",1701644054041],"a87a1c61-00ba-4c7a-8e90-97f0ce5c5ced",{"_118":218,"_143":-5,"_116":219,"_113":220},7,["D",1701643941146],"f927f78f-8dac-4002-a3c2-1ca8bef034db",{"_118":222,"_143":-5,"_116":223,"_113":224},6,["D",1701643795685],"732fab93-c331-4df1-9af1-b765399a6692",{"_118":226,"_143":-5,"_116":227,"_113":228},5,["D",1701643718583],"73c0b5e8-ef8a-45bb-a6f9-27cc9d9a903c",{"_118":230,"_143":-5,"_116":231,"_113":232},4,["D",1701643693138],"99590e74-39b9-413c-9250-0ce08bd256b7",{"_118":234,"_143":-5,"_116":235,"_113":236},3,["D",1701643562950],"e31d91e8-8ffb-467b-9923-a2721700acc4",{"_118":90,"_143":-5,"_116":238,"_113":239},["D",1701643510471],"b0985009-d3a7-4762-a86e-510e06572076",{"_118":123,"_143":-5,"_116":241,"_113":242},["D",1701638159737],"e2a9f2bb-c9ab-49dd-8f84-922d46c95a02",{"_118":31,"_143":-5,"_116":244,"_113":245},["D",1701638087295],"a1d92ba8-87eb-4731-9a04-7ed8b70a654a","recentThread","breadcrumbs","comments",[],"isOwner","routes/_app.v.$handle.$name.forks",{"_253":254,"_310":123,"_311":137,"_312":31,"_94":313},"forksList",[255],{"_100":256,"_257":258},"40e58ff5-f8dc-4ce9-87ce-afc26b2f311b","initialData",{"_98":259,"_95":96,"_100":256,"_102":103,"_104":-5,"_105":106,"_107":-5,"_108":109,"_110":260,"_112":26,"_113":260,"_114":261,"_116":262,"_118":263,"_120":26,"_121":31,"_124":123,"_125":123,"_126":31,"_122":31,"_127":31,"_128":-5,"_20":264,"_134":265,"_135":-7,"_138":139,"_267":-5,"_136":268,"_140":269},"retrievalPractice","fcb1e55a-b7be-11ee-ad58-325518e2651b","/** @jsxImportSource https://esm.sh/react */\nimport { generateLessonHtml } from \"https://esm.town/v/petermillspaugh/lessonTemplate\";\nimport { renderToString } from \"npm:react-dom/server\";\n\n/*\n * Work-in-progress! 👷‍♂️\n */\n\nconst TITLE = \"Retrieval practice\";\n\nconst FILL_BLANK = (\n <>\n We often hear things like, \"I am a visual learner,\" or \"the way I learn best is by re-reading my notes and\n underlining key concepts.\" Do you think there is any merit to personal preference of learning style? Why or why not?\n \n);\n\nconst CONTENT = (\n <>\n

About this course

\n The main purpose of this course is to teach you about about effective, research-backed learning techniques covered\n in the book{\" \"}\n \n Make It Stick\n . The secondary purpose of this course is to provide a copyable template for creating email-based courses with\n a structure informed by effective learning techniques covered in that book. If you know some JavaScript/HTML and\n are interested in that, all the code is public and{\" \"}\n \n I wrote about the implementation on my digital garden\n .\n

\n As a disclaimer, I am not a learning expert. I like to learn, and I like learning about learning. As mentioned\n just above, this course is a distillation of{\" \"}\n Make It Stick, supported by some follow-up research I did. It's also a way for me to strengthen what I\n learned from the book. If you have any feedback on the course please shoot me an email at\n pete@petemillspaugh.com—I'm open to suggestions, corrections, or anything else you'd like to share.\n

\n\n {/*

Is rereading an effective learning tactic?

*/}\n {/*

Massed practice

*/}\n {/*

Rereading is not effective.

*/}\n {\n /*

\n We are poor judges of when we are learning well and when we are not. A good example of this for me is when I take\n an online coding course or tutorial on a new technology/tool, writing lots of caffeine-fueled notes and not\n self-testing nor applying that new technology to a project. The good feeling from cruising through content and\n taking notes is illusory—durable learning requires retrieval and application.\n

*/\n }\n\n

📣 This course is still a work-in-progress 📣

\n Thank you for signing up to test things out! I'm still working on the course content, so this lesson is\n incomplete, but lmk any thoughts or suggestions you have in the meantime.\n

\n\n

What is retrieval practice?

\n Retrieval practice{\" \"}\n is cognitive psychology's term for the act of recalling something from memory. Studying flashcards is a very\n structured form of retrieval practice, but we retrieve things all the time—like when a friend asks you about the\n book you're reading, when you cook a recipe without referencing instructions, or when speaking in another language\n that you don't use often.\n

\n As chapter 2 of Make It Stick—\"To Learn, Retrieve\"—puts it:\n

\n \n Retrieval practice—recalling facts or concepts or events from memory—is a more effective learning strategy than\n review by rereading. Flashcards are a simple example. Retrieval strengthens the memory and interrupts\n forgetting. A single, simple quiz after reading a text or hearing a lecture produces better learning and\n remembering than rereading the text or reviewing lecture notes.\n \n

\n Each lesson in this course starts with a fill-in-the-blank question and ends with a set of review questions and\n reflection. This structure is deliberately designed to force retrieval practice. Not only that, but retrieval\n should be spaced, which is the topic of the next lesson and the reason this course includes a one-day delay before\n sending the following lesson. From chapter 2 of the book:\n

\n \n When retrieval practice is spaced, allowing some forgetting to occur between tests, it leads to stronger long-\n term retention than when it is massed.\n \n

\n\n

Brain food: retrieval as reconsolidation

\n {/*

Your brain reconsolidates memory upon recall.

*/}\n

From the book:

\n \n While the brain is not a muscle that gets stronger with exercise, the neural pathways that make up a body of\n learning do get stronger, when the memory is retrieved and the learning is practiced. Periodic practice arrests\n forgetting, strengthens retrieval routes, and is essential for hanging onto the knowledge you want to gain.\n \n

\n\n {/*

This is too hard

*/}\n {/*

Effortful retrieval

*/}\n\n {/*

Should I try this at my school?

*/}\n {/*

In 2005, the authors of Make It Stick (who are cognitive psychologists) conducted a study of retrieval practice at Columbia Middle School in Illinois (go Eagles!).

*/}\n\n

But I'm a visual learner

\n {/* TODO: 2008 study mentioned on page 145 */}\n

\n Returning to the question from the start of this lesson, is there any evidence that instruction in one’s preferred\n learning style (e.g. \"visual learner\") improves learning outcomes?\n

From the book:

\n \n The popular notion that you learn better when you receive instruction in a form consistent with your preferred\n learning style, for example as an auditory or visual learner, is not supported by the empirical research. People\n do have multiple forms of intelligence to bring to bear on learning, and you learn better when you “go wide,”\n drawing on all of your aptitudes and resourcefulness, than when you limit instruction or experience to the style\n you find most amenable.\n \n

That said, learning style should match the subject matter. Back to the book:

\n \n It is more important that the mode of instruction match the nature of the subject being taught: visual\n instruction for geometry and geography, verbal instruction for poetry, and so on. When instructional style\n matches the nature of the content, all learners learn better, regardless of their differing preferences for how\n the material is taught.\n \n

\n \n);\n\nconst QUIZ = [\n {\n question: \"What is retrieval practice?\",\n answer: \"Retrieval practice is the act of recalling facts or concepts or events from memory.\",\n },\n {\n question:\n \"Is there any evidence that instruction in one’s preferred learning style (e.g. visual) improves learning outcomes?\",\n answer:\n \"No, there is no research supporting these claims. Learning style should match the subject matter, though (e.g. visual for geometry).\",\n },\n];\n\nexport const retrievalPractice = {\n title: TITLE,\n fillBlank: FILL_BLANK,\n quiz: QUIZ,\n fetchHtml: (email: string, lesson: number) =>\n generateLessonHtml({\n email,\n lesson,\n title: `Lesson ${lesson + 1}: ${TITLE}`,\n fillBlank: FILL_BLANK,\n content: CONTENT,\n quiz: QUIZ,\n }),\n};",["D",1705774140624],49,{"_130":131,"_132":133},{"_113":200,"_130":131,"_98":99,"_118":198,"_266":-5},"prDisabledHint","latestEvaluation","petermillspaugh/retrievalPractice",[270,274,278,282,286,290,294,298,302,306],{"_116":271,"_118":263,"_272":273},["D",1705774140624],"n","1",{"_116":275,"_118":276,"_272":277},["D",1705774127322],48,"2",{"_116":279,"_118":280,"_272":281},["D",1705774064910],47,"3",{"_116":283,"_118":284,"_272":285},["D",1705773979637],46,"4",{"_116":287,"_118":288,"_272":289},["D",1705773708647],45,"5",{"_116":291,"_118":292,"_272":293},["D",1705773628450],44,"6",{"_116":295,"_118":296,"_272":297},["D",1705773616759],43,"7",{"_116":299,"_118":300,"_272":301},["D",1705773492614],42,"8",{"_116":303,"_118":304,"_272":305},["D",1705772780224],41,"9",{"_116":307,"_118":308,"_272":309},["D",1705772690819],40,"10","forksCount","valname","page",{"_113":111,"_98":99,"_130":131,"_11":96,"_118":119,"_100":101,"_114":115,"_105":106,"_112":26,"_136":137},"routes/_app","actionData","errors"]