Thinking Outside the Neurotypical Box: A Gestalt Processor's Guide to Takin the RICA
Preparing for the Reading Instruction Competence Assessment (RICA) in California can be a daunting task, especially for those who struggle with creating written responses under the pressure of a timed test. As an autistic gestalt processor (aka, non-verbal), I find it particularly challenging to generate these responses on demand. However, I am leveraging an “old friend” to help me prepare for the RICA’s constructed response questions: Large Language Models (LLMs).
LLMs, such as ChatGPT and others, are, after all, data systems capable of generating human-like text based on given prompts. By leveraging the power of these models, I can create sample responses to practice with, allowing me to build fluency and confidence in answering the types of questions found on the RICA, particularly those in Subtest 1 (which I’m taking next week).
In today’s article, I will explore how LLMs can be used to generate practice material for the RICA’s constructed response questions. I will also discuss how the strategies of “repeated reading” and “spaced repetition” can be applied to the generated responses, helping to solidify understanding and improve recall during the actual test. As an autistic gestalt processor, I find these strategies essential in overcoming the challenges posed by timed, written assessments.
By the end of this article, I hope you will have a better understanding of how LLMs can be utilised to create personalised study materials for the RICA (or any of the CSETs), and how these tools, combined with effective study strategies, can help individuals build the skills and confidence needed to succeed on this important assessment.
Preparing for the RICA
Preparing for the RICA can be a daunting task, particularly when it comes to the constructed response questions. These questions require candidates to demonstrate their knowledge and understanding of reading instruction by crafting well-structured, comprehensive responses within a limited timeframe. The challenge lies not only in possessing a deep understanding of the content but also in the ability to articulate that knowledge effectively in writing, all under the pressure of a timed test.
For autistic individuals who are gestalt processors (like me), the difficulties posed by the RICA’s constructed response questions can be even more pronounced. Gestalt processors tend to think in terms of the big picture, often struggling to break down information into smaller, more manageable parts. This cognitive style can make it challenging to organise thoughts and ideas quickly and efficiently, which is essential when working under time constraints. Moreover, the pressure of the timed testing environment can exacerbate feelings of anxiety and overwhelm, further complicating the task at hand.
Faced with these challenges, folks like me may find themselves seeking innovative ways to prepare for the RICA’s constructed response questions. One promising avenue is the use of LLMs as a study tool. As I hope you’re aware of by now, LLMs are advanced data systems capable of generating human-like text, offering a unique opportunity to create personalised practice materials tailored to the specific needs and learning style of the individual. By leveraging the power of LLMs, we can generate sample responses, engage in targeted practice, and build the skills and confidence needed to succeed on the RICA.
This article will focus specifically on Subtest 1 of the RICA, which assesses candidates’ knowledge of word analysis and fluency. Subtest 1 requires a thorough understanding of concepts such as phonics, morphology, and sight words, as well as the ability to apply this knowledge to help students develop fluency in reading. By concentrating on this specific subtest, we can explore how LLMs can be used to generate targeted practice materials that address the unique demands of Subtest 1, ultimately helping candidates feel more prepared and confident as they approach this critical portion of the RICA.
Understanding Large Language Models
Remember that LLMs are data processing systems that have been trained on vast amounts of text data to generate human-like responses to given prompts. These models use deep learning algorithms to analyse patterns in the training data, allowing them to understand and generate language in a way that closely mimics human writing. LLMs work by taking a prompt or input text and predicting the most likely next word or sequence of words based on the patterns it has learned from the training data. This process is repeated iteratively, allowing the model to generate coherent and contextually relevant text.
One of the most well-known LLMs is GPT-4 (Generative Pre-trained Transformer 4), developed by OpenAI. GPT-4 has been trained on an enormous corpus of text data, making it capable of generating highly sophisticated and human-like responses across a wide range of topics and styles. Other notable LLMs include BERT (Bidirectional Encoder Representations from Transformers) by Google, and XLNet, developed by Google and Carnegie Mellon University. These models have been used in various applications, from language translation and sentiment analysis to content generation and question-answering systems.
The power of LLMs lies in their ability to generate text that closely resembles human writing. When given a specific prompt, such as a question or a topic statement, LLMs can produce coherent, well-structured responses that demonstrate a deep understanding of the subject matter. This capability makes LLMs particularly useful for creating practice materials for assessments like the RICA, where the ability to generate comprehensive, context-specific responses is essential.
By leveraging LLMs, folks can create targeted practice prompts that focus on specific aspects of the RICA’s constructed response questions. For example, a prompt could be designed to elicit a response that demonstrates understanding of phonics instruction or strategies for promoting reading fluency. The LLM can then generate multiple sample responses to this prompt, providing the learner with a wealth of practice material to work with. These generated responses can serve as models for understanding the structure, content, and style expected in the actual test, allowing the learner to internalise these elements through repeated exposure and practice.
Moreover, the use of LLMs for generating practice responses allows for a high degree of customisation and flexibility. Prompts can be easily modified or adapted to target specific areas of weakness or to provide additional challenge as the learner progresses. This adaptability is particularly valuable for autistic gestalt processors or folks with Specific Learning Disabilities (SLDs), who may require a more personalised approach to test preparation that takes into account their unique learning needs and preferences.
Using LLMs to Generate Practice Material for the RICA
To effectively use LLMs for generating practice material for the RICA, it is essential to craft prompts that are specific, clear, and aligned with the content and structure of the test. When creating prompts for Subtest 1, which focuses on word analysis and fluency, prompts should be designed to elicit responses that demonstrate a deep understanding of these concepts and their application in reading instruction. For example, a prompt could ask the LLM to describe a lesson plan for teaching phonics to struggling readers, or to explain the importance of morphological awareness in developing reading fluency. By carefully constructing prompts that target key aspects of word analysis and fluency, we can ensure that the generated responses are directly relevant to the content of Subtest 1.
Whilst LLMs are capable of generating highly sophisticated and contextually relevant responses, it is important to tailor these responses to the specific requirements of Subtest 1. This may involve providing additional guidance or constraints within the prompt to ensure that the generated response aligns with the expectations of the test. For instance, prompts could specify the desired length of the response, the key points that should be addressed, or the type of examples that should be included. By incorporating these specific guidelines into the prompts, candidates can help to ensure that the generated responses are not only relevant to the content of Subtest 1 but also adhere to the structural and stylistic conventions of the test.
Whilst LLMs are powerful tools for generating practice material, it is crucial to carefully review and evaluate the generated responses to ensure their quality and relevance. Users of LLMs should always critically examine each response, checking for accuracy, coherence, and alignment with the specific requirements of Subtest 1. In some cases, it may be necessary to revise or refine the generated responses to better suit the needs of the learner. This may involve editing for clarity, adding additional examples or explanations, or adjusting the structure of the response to more closely mirror the expectations of the test. By engaging in this process of review and refinement, candidates can ensure that the practice material generated by the LLM is of high quality and effectively supports their preparation for Subtest 1.
Ultimately, the use of LLMs to generate practice material for the RICA offers a powerful tool for anyone seeking to build their skills and confidence in successfully navigating the constructed response sections. By crafting targeted prompts, tailoring responses to the specific requirements of the subtests, and ensuring the quality and relevance of the generated content, learners can create a wealth of personalised practice material that supports their unique learning needs and helps them to succeed on this critical assessment.
Implementing Effective Study Strategies
Implementing effective study strategies is crucial for candidates preparing for the RICA, particularly when using LLM-generated practice materials. Two powerful strategies that can enhance learning and retention are “repeated reading” and “spaced repetition.”
Repeated reading is a strategy that involves reading a text multiple times to improve fluency, comprehension, and familiarity with the content. When applied to the practice materials generated by LLMs, candidates can read and reread the sample responses to internalise the key concepts, structures, and terminology related to the focus elements. This repetition helps to reinforce understanding and builds confidence in the candidate’s ability to articulate their knowledge effectively.
To implement repeated reading, candidates should set aside dedicated study sessions to focus on the generated practice materials. During these sessions, they should read each sample response carefully, paying attention to the main ideas, supporting details, and examples provided. After the initial reading, candidates should reread the response, striving to deepen their understanding and commit the key points to memory. This process can be repeated several times until the candidate feels confident in their grasp of the material.
Spaced repetition is another effective strategy that involves reviewing learned material at increasing intervals over time. This approach takes advantage of the psychological principle that information is more likely to be retained when it is revisited at strategically spaced intervals. By applying spaced repetition to the LLM-generated practice materials, candidates can systematically review and reinforce their understanding of word analysis and fluency concepts.
To implement spaced repetition, candidates can create a study schedule that incorporates regular review sessions at gradually increasing intervals. For example, after initially studying a set of practice materials, the candidate might review the same materials one day later, then three days later, then a week later, and so on. This spacing helps to solidify the information in long-term memory and ensures that the candidate maintains a strong grasp of the content over time.
The combination of repeated reading and spaced repetition can be particularly beneficial for candidates preparing for the RICA. By actively engaging with the LLM-generated practice materials through repeated exposure and strategic review, candidates can develop a deep, enduring understanding of the key concepts and skills assessed in the subtests. Moreover, these strategies can help to alleviate test anxiety by building familiarity and confidence with the material, allowing candidates to approach the exam with greater self-assurance and poise.
Ultimately, the use of repeated reading and spaced repetition in conjunction with LLM-generated practice materials offers a powerful, personalised approach to preparing for the RICA. By leveraging these strategies, candidates can optimise their learning, retain essential knowledge, and develop the skills necessary to succeed on this critical assessment.
Putting It All Together: A Step-by-Step Guide
To effectively use LLMs for generating practice materials and implement the strategies of repeated reading and spaced repetition, candidates can follow a step-by-step guide to ensure a systematic and efficient approach to their RICA preparation.
The first step is to set up an LLM for generating practice materials. Candidates can choose from a variety of LLMs, such as GPT-4, BERT, or XLNet, depending on their accessibility and ease of use. Once the LLM is selected, candidates should familiarise themselves with the model’s capabilities and input requirements to ensure they can effectively utilize it for generating practice content.
Next, candidates should focus on creating prompts that will elicit sample responses relevant to the content and structure of Subtest 1. These prompts should be carefully crafted to target key aspects of word analysis and fluency, such as phonics instruction, morphological awareness, and strategies for developing reading fluency. Candidates should aim to create a diverse set of prompts that cover a wide range of topics and question types to ensure comprehensive preparation.
After generating sample responses using the LLM, candidates should organise the content in a way that facilitates effective studying. This may involve categorising responses by topic, difficulty level, or question type, and creating a study plan that allows for systematic review and progression. Candidates may also find it helpful to use tools like flashcards or mind maps to visualise and internalize the key concepts and ideas present in the generated content.
With the practice materials organised and a study plan in place, candidates can begin implementing the strategies of repeated reading and spaced repetition. For repeated reading, candidates should dedicate study sessions to carefully reading and rereading each sample response, focusing on understanding the main ideas, supporting details, and examples provided. This process should be repeated until the candidate feels confident in their grasp of the material.
To implement spaced repetition, candidates should create a review schedule that incorporates revisiting the practice materials at gradually increasing intervals. This may involve reviewing a subset of the generated responses one day after initial study, then three days later, a week later, and so on. By strategically spacing out their review sessions, candidates can reinforce their understanding and retention of the key concepts over time.
Throughout the study process, candidates should track their progress and adjust their study plan as needed. This may involve assessing their comfort level with different topics, identifying areas where additional practice is needed, and modifying their review schedule accordingly. By remaining flexible and responsive to their own learning needs, candidates can ensure that they are making the most of their study time and progressing toward mastery of the material.
By following this step-by-step guide (or your own version), candidates can harness the power of LLMs and effective study strategies to create a personalised, efficient approach to preparing for the RICA subtest constructed response sections. Through a combination of targeted practice, repeated exposure, and strategic review, candidates can build the knowledge, skills, and confidence necessary to succeed on this critical assessment and move one step closer to their goal of becoming certified reading instructors.
Sample prompts and responses
With ChatGPT-4, I’ve found it helpful to “warm up” the LLM with some introductory questions. This allows me to gauge if it’s on the right track, correcting it if / when necessary. My first three prompts accomplish this task with no errors.
Tell me about the RICA test in California.
Tell me about Subtest 1.
Tell me more about the constructed response tasks.
I then ask: Can you create a sample response for the word analysis prompt?
Result: Creating a sample response for a constructed-response task focused on Word Analysis (Domain 2) for the RICA can provide insight into what an effective answer might include. The prompt for this task might ask the candidate to describe instructional strategies for teaching word analysis skills to students struggling with reading.
**Sample Response:**
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"In addressing challenges students face with word analysis, my strategy integrates both explicit instruction and hands-on activities to reinforce phonemic awareness, decoding skills, and the application of phonics rules in reading. Initially, I would introduce a mini-lesson focused on a specific phonics rule, such as the silent 'e' rule or common vowel digraphs. This would involve direct explanation of the rule, followed by examples where the rule applies.
To reinforce the lesson, students would engage in sorting activities where they categorize words based on the phonics rule of the day. For example, sorting words into groups whether they have a long vowel sound because of a silent 'e' or because of a vowel digraph.
Further, incorporating technology, students would use reading apps that offer interactive games focusing on phonics patterns and word analysis skills. These activities allow for individualized pacing and immediate feedback, essential for skill mastery.
Finally, to apply these skills in context, students would participate in guided reading sessions. During these sessions, I would prompt them to identify and decode unfamiliar words using the phonics rules we've covered. This contextual application solidifies their understanding and ability to use word analysis skills during independent reading.
Assessment of students' progress would be ongoing, utilizing both informal observations during activities and formal measures such as reading inventories focused on phonics and decoding skills. Based on assessment results, instruction would be adjusted to meet the evolving needs of the students, ensuring all have the foundational word analysis skills necessary for reading proficiency."
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This sample response outlines a clear strategy that incorporates explicit teaching, practical application, technology integration, and assessment to address the teaching of word analysis skills. It demonstrates an understanding of effective instructional practices in reading and the ability to apply these practices to support student learning.
I ask for a more specific response: How about a sample for word analysis that deals with the problem of improper syllabication?
Response: Addressing the challenge of improper syllabication, a skill crucial for decoding unfamiliar words, requires a structured approach to teaching word analysis. Here’s a sample response focusing on this issue for a RICA constructed-response task:
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"To address the challenge of improper syllabication, which impedes reading fluency and comprehension, I propose a multi-step instructional strategy. This strategy emphasizes explicit teaching, guided practice, and application of syllabication rules in a supportive learning environment.
Initially, I would introduce the concept of syllables through direct instruction, explaining that a syllable is a word part containing a vowel sound. Utilizing visual aids, I would demonstrate how words can be broken down into syllables, highlighting the role of vowels and consonants. This introduction sets a foundation for understanding syllabication as a strategy for decoding words.
Following the introduction, I would focus on teaching specific syllabication rules, such as identifying vowel-consonant-vowel patterns, recognizing compound words, and understanding the role of consonant blends and digraphs in forming syllables. Each rule would be introduced in a separate lesson to avoid overwhelming students with too much information at once. Activities would include segmenting words into syllables using manipulatives, such as counters or blocks, to represent syllables visually.
To reinforce these rules, students would engage in guided practice with immediate feedback. This could involve interactive games that require students to divide words into syllables correctly to advance. Additionally, students could work in pairs to segment words, fostering peer learning and collaboration.
Incorporating technology, I would utilize educational apps that offer syllabication exercises, allowing for differentiated instruction based on individual student needs. These apps can provide immediate corrective feedback and adapt to each student's learning pace, offering a personalized learning experience.
To apply syllabication skills in context, I would integrate reading activities that encourage students to use these skills when encountering unfamiliar words in texts. Guided reading sessions would provide opportunities for students to practice syllabication with teacher support, gradually moving towards independent application in their reading.
Finally, to assess students' mastery of syllabication, I would conduct informal assessments through observation during activities and formal assessments using word lists or passages. Students would be asked to identify and divide words into syllables, with a focus on applying the syllabication rules they have learned.
By systematically teaching syllabication rules, providing varied practice opportunities, and reinforcing these skills in reading activities, students will develop a critical decoding strategy that supports reading fluency and comprehension."
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This response outlines a comprehensive instructional strategy focused on teaching and reinforcing syllabication rules to address the problem of improper syllabication, demonstrating an understanding of effective reading instruction techniques.
I then switch to fluency: Can you create a sample response for the fluency prompt?
Response: For a constructed-response task focused on Fluency (Domain 3) in the RICA examination, the prompt might ask the candidate to describe a plan to improve reading fluency in a group of students who are reading below grade level.
**Sample Response:**
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"To enhance reading fluency among students reading below grade level, my approach would encompass a multifaceted strategy aimed at improving accuracy, rate, and prosody, thereby enabling smoother and more expressive reading.
Firstly, I would implement repeated reading sessions, where students read the same text multiple times. Initially, I would model reading the text aloud, demonstrating fluent reading by paying attention to punctuation, intonation, and rhythm. Students would then engage in choral reading, followed by partner reading, and finally, individual silent reading. This method allows students to become familiar with the text, reducing decoding errors and increasing their reading speed over time.
To address individual needs, I would organize fluency centers equipped with a variety of leveled and high-interest texts, allowing students to practice with materials appropriate for their reading level. Each center would also include audio recordings of the texts, enabling students to listen to fluent reading and practice along, which helps in improving their prosody and comprehension.
Additionally, I would incorporate fluency mini-lessons focused on specific aspects such as pacing, pausing, and expression. These lessons would involve short, targeted practices using poems, dialogues, and passages that lend themselves to expressive reading. Through these exercises, students would learn to adjust their reading pace, use appropriate pauses for punctuation, and modulate their voices to reflect the mood and tone of the text.
To monitor progress, I would conduct regular fluency assessments using timed reading passages followed by comprehension questions. This would not only allow me to track improvements in reading speed and accuracy but also ensure that increased fluency is translating into better comprehension.
Lastly, to foster a positive reading culture and motivate students, I would celebrate their fluency achievements through a 'Fluency Wall of Fame,' where students' progress and successes are displayed. This recognition would serve to encourage continued practice and improvement.
By employing a structured yet flexible approach that incorporates modeling, practice, and feedback, this plan aims to enhance fluency skills, thereby contributing to overall reading improvement and fostering a more confident and competent group of readers."
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This response offers a comprehensive strategy tailored to address the fluency needs of struggling readers. It combines evidence-based practices with engaging activities, ensuring a balanced focus on accuracy, rate, and expression in reading.
As before, I get more specific: How about another for fluency that uses repeated reading and spaced repetition?
Response: To enhance fluency through repeated reading and spaced repetition, a strategic approach that balances intensive practice with systematic review over time is necessary. Here’s how an effective response to a RICA constructed-response task on this topic might look:
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"Improving reading fluency in students who struggle with reading speed, accuracy, and expression requires a focused strategy that leverages the benefits of repeated reading and spaced repetition. My plan involves integrating these methods into a comprehensive fluency development program.
Firstly, I would implement a repeated reading program where students are encouraged to read and reread short, engaging texts that are slightly below their independent reading level. This activity starts with a teacher read-aloud to model fluent reading. Students then engage in echo reading, where they mimic the teacher's pace, tone, and expression. Following this, students would participate in choral reading of the same text, promoting unity and reducing individual anxiety about reading aloud.
Subsequently, students would be paired for partner reading, allowing them to practice the text multiple times with a peer. This step not only reinforces fluency but also builds confidence. The final stage of the repeated reading session involves students reading the text silently, focusing on internalizing fluency skills.
To incorporate spaced repetition into the fluency program, I would schedule the repeated reading activities to recur at systematically increasing intervals. For example, after the initial reading session, students would revisit the same text after two days, then after four days, and subsequently after a week. This method helps to consolidate memory and improve long-term retention of fluency skills.
Furthermore, to track progress and motivate students, I would introduce a fluency portfolio for each student. This portfolio would include recordings of their readings over time, allowing students to self-assess their improvement in speed, accuracy, and expression. It would also serve as a tool for setting individual fluency goals and celebrating achievements.
To ensure the effectiveness of this strategy, I would monitor student progress through regular fluency assessments, using tools such as timed one-minute reads followed by comprehension questions to ensure that fluency gains are not at the expense of comprehension.
By combining repeated reading with spaced repetition and integrating assessment and self-reflection, this fluency enhancement plan is designed to systematically improve students' reading fluency, leading to more confident and proficient readers."
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This sample response outlines a structured and evidence-based approach to fluency improvement, highlighting the use of repeated reading and spaced repetition, along with monitoring and self-reflection mechanisms to track and motivate student progress.
Notice: In each response, it sort of restates the request. Then, at the end, it tells me that it accomplished it’s task successfully.
Final thoughts …
To wrap this up, the use of LLMs for generating practice materials, combined with the implementation of effective study strategies like repeated reading and spaced repetition, offers a powerful, personalised approach to preparing for the RICA subtests. By leveraging the capabilities of LLMs to create targeted, high-quality practice content, candidates can develop a deep understanding of the key concepts and skills related to word analysis and fluency.
Moreover, the ability to tailor the practice materials to one’s individual learning needs and preferences is particularly valuable for candidates who may benefit from a more customised approach to test preparation (like me). By crafting prompts that target specific areas of weakness or interest, and by adjusting the difficulty and complexity of the generated responses, candidates can create a study plan that is optimally suited to their unique learning style and goals.
It is important to recognise that the effectiveness of this approach may vary from person to person, and what works well for one candidate may not be the best fit for another. Therefore, candidates are encouraged to experiment with different LLMs, prompt structures, and study strategies to find the combination that works best for them. This may involve a period of trial and error, but the process of self-discovery and adaptation is an essential part of developing a truly personalised and effective approach to test preparation. Along these lines, though I like Claude for some tasks, it’s lack of updated material / internet access hinders it’s abilities for this task. For my work on creating practice materials, I used ChatGPT4.
Ultimately, the integration of LLMs and “research-backed study strategies” offers a promising avenue for candidates seeking to navigate the challenges posed by the RICA subtests, which are fundamentally ableist in their design. It is crucial to acknowledge that the grading rubric used by evaluators is inherently ableist, favoring a neurotypical approach to language and communication that may not align with the lived experiences of neurodivergent candidates. Furthermore, the training data used to develop LLMs like GPT-4 is largely derived from ableist sources, perpetuating a normative standard that fails to capture the diversity of human cognition and expression.
For Gestalt Language Processors and other neurodivergent candidates, the RICA’s constructed response questions may feel particularly alienating, as they often fail to reflect or validate our unique perspectives and ways of processing information. However, by leveraging the power of LLMs to generate practice responses that conform to the ableist expectations of the test, whilst simultaneously engaging in critical self-reflection and advocacy, candidates can develop strategies for success that both acknowledge and challenge the limitations of the current assessment paradigm.
Ultimately, whilst the RICA may not speak to the lived experiences of neurodivergent candidates, the strategic use of LLMs and personalised study techniques can serve as a valuable tool for navigating an ableist system and demonstrating one’s competence as a reading instructor. By remaining critical of the test’s inherent biases, whilst also harnessing the power of technology to meet its demands, candidates can chart a path toward success that honors their own unique strengths and challenges, and lays the groundwork for a more inclusive and equitable approach to reading instruction in the future.