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    "# Preview\n",
    "\n",
    "- Use these questions before class to check your familiarity with the chapter glossary and core terms.\n",
    "- Sign in from the account menu before you start answering the questions.\n",
    "- Multiple submissions are allowed. The highest score is kept.\n",
    "\n",
    "Review the [Chapter 15 glossary](../1500-clustering.ipynb) before class. These ten questions mix multiple-choice and true/false: seven recognize terms and three connect related ideas. No calculations or code tracing are required.\n"
   ]
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   "id": "ch08-preview-quiz",
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    "\n",
    "<div class='ch15-preview-quiz' id='ch15-preview-quiz' data-question-set-version='dsm-ch15-preview-2026-10-19-v2'>\n",
    "  <p>Earlier submissions and best scores are retained. If you already completed this Preview, you do not need to repeat it; you may retry the revised questions.</p>\n",
    "  <div id='ch15-preview-questions'></div>\n",
    "  <div class='ch15-preview-actions'>\n",
    "    <button type='button' id='ch15-preview-submit' disabled>Submit</button>\n",
    "    <button type='button' class='secondary' id='ch15-preview-reset'>Reset</button>\n",
    "    <span class='ch15-preview-result' id='ch15-preview-result' aria-live='polite'></span>\n",
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    "\n",
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    "\n",
    "  function draftAnswers(quiz) {\n",
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    "  var questions = [\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: Clustering requires a known target label for every observation before groups can be formed.\",\n",
    "    \"concepts\": [\n",
    "      \"Clustering\",\n",
    "      \"Unsupervised learning\"\n",
    "    ],\n",
    "    \"explanation\": \"False. Clustering is an unsupervised approach: it forms groups from similarity in selected features without requiring known target labels for the observations.\",\n",
    "    \"retry_hint\": \"Compare clustering with supervised tasks that learn from known target labels.\",\n",
    "    \"id\": \"q1\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1501-clustering-concepts.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: A cluster is a group of observations that are similar according to the chosen features and comparison rule.\",\n",
    "    \"concepts\": [\n",
    "      \"Cluster\",\n",
    "      \"Distance metric\"\n",
    "    ],\n",
    "    \"explanation\": \"True. A cluster groups observations judged similar under a chosen representation and rule. The features and comparison rule matter; changing them can change the resulting groups.\",\n",
    "    \"retry_hint\": \"Review how the meaning of similarity depends on the representation of observations.\",\n",
    "    \"id\": \"q2\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1501-clustering-concepts.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"Which clustering method asks for a chosen number of groups and represents each group by a center?\",\n",
    "    \"concepts\": [\n",
    "      \"K-means\",\n",
    "      \"Centroid\"\n",
    "    ],\n",
    "    \"explanation\": \"K-means partitions observations into a specified number of clusters, represented by centroids. Classification and regression use a target outcome, while an A/B test compares assigned conditions.\",\n",
    "    \"retry_hint\": \"Identify the method that forms a specified number of groups around centers.\",\n",
    "    \"id\": \"q3\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1502-k-means-workflow.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"A nearest-neighbor classifier with known target labels\",\n",
    "      \"B\": \"A regression line for a numerical target\",\n",
    "      \"C\": \"A randomized A/B test\",\n",
    "      \"D\": \"K-means\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"What is the center of a k-means cluster called?\",\n",
    "    \"concepts\": [\n",
    "      \"Centroid\",\n",
    "      \"K-means\"\n",
    "    ],\n",
    "    \"explanation\": \"A centroid is the center representing a k-means cluster. It is updated from the observations assigned to that cluster. A cluster label names a group; a distance metric defines how observations are compared.\",\n",
    "    \"retry_hint\": \"Distinguish the point representing a group from its identifier and measures of variation or distance.\",\n",
    "    \"id\": \"q4\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1502-k-means-workflow.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Cluster label\",\n",
    "      \"B\": \"Within-cluster variation\",\n",
    "      \"C\": \"Distance metric\",\n",
    "      \"D\": \"Centroid\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: The k-means assignment step places observations with their nearest current centroids.\",\n",
    "    \"concepts\": [\n",
    "      \"Assignment step\",\n",
    "      \"Centroid\"\n",
    "    ],\n",
    "    \"explanation\": \"True. The assignment step associates observations with the nearest current center. The update step then recalculates the centers from their assigned observations.\",\n",
    "    \"retry_hint\": \"Compare the step that assigns observations with the step that recalculates centers.\",\n",
    "    \"id\": \"q5\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1502-k-means-workflow.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"After observations have been assigned to clusters, which k-means step recalculates their centers?\",\n",
    "    \"concepts\": [\n",
    "      \"Update step\",\n",
    "      \"Assignment step\"\n",
    "    ],\n",
    "    \"explanation\": \"The update step recalculates centroids from the assigned observations. K-means alternates assignment and update, so moving centers and assigning observations are connected but distinct operations.\",\n",
    "    \"retry_hint\": \"Identify whether observations are being assigned or centers are being recalculated.\",\n",
    "    \"id\": \"q6\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1502-k-means-workflow.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Assignment step\",\n",
    "      \"B\": \"Initialization\",\n",
    "      \"C\": \"Update step\",\n",
    "      \"D\": \"Feature scaling\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: A silhouette score compares how well observations fit their own clusters with how separated they are from other clusters.\",\n",
    "    \"concepts\": [\n",
    "      \"Silhouette score\",\n",
    "      \"Within-cluster variation\"\n",
    "    ],\n",
    "    \"explanation\": \"True. Silhouette compares within-cluster fit with separation from other clusters. It can support comparison of clustering results, but it does not replace a judgment about whether the groups are useful.\",\n",
    "    \"retry_hint\": \"Review the two relationships a silhouette score compares.\",\n",
    "    \"id\": \"q7\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"reading\": \"../1503-interpreting-clusters.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"Annual spending values are in the thousands of dollars, while order counts are usually only a few dozen. Which idea addresses their different numerical scales before distance-based clustering?\",\n",
    "    \"concepts\": [\n",
    "      \"Feature scaling\",\n",
    "      \"Distance metric\"\n",
    "    ],\n",
    "    \"explanation\": \"Feature scaling transforms variables so their scales are more comparable. This helps prevent a large numerical scale from dominating distance simply because of its measurement units.\",\n",
    "    \"retry_hint\": \"Connect how distances use feature values with the units used to record those values.\",\n",
    "    \"id\": \"q8\",\n",
    "    \"cognitive_level\": \"connection\",\n",
    "    \"reading\": \"../1503-interpreting-clusters.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Choosing a larger number of clusters\",\n",
    "      \"B\": \"Renaming the cluster identifiers\",\n",
    "      \"C\": \"Feature scaling\",\n",
    "      \"D\": \"Repeating the fit without changing feature units\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"prompt\": \"A clustering result has clear numerical separation, but the manager asks whether the groups support useful customer actions. Which additional consideration is needed?\",\n",
    "    \"concepts\": [\n",
    "      \"Domain judgment\",\n",
    "      \"Segmentation\",\n",
    "      \"Interpretability\"\n",
    "    ],\n",
    "    \"explanation\": \"Domain judgment asks whether the groups make sense and support useful decisions in the application. Good numerical separation alone does not establish that a segmentation is meaningful or actionable.\",\n",
    "    \"retry_hint\": \"Separate a technical grouping measure from the practical meaning of the groups.\",\n",
    "    \"id\": \"q9\",\n",
    "    \"cognitive_level\": \"connection\",\n",
    "    \"reading\": \"../1503-interpreting-clusters.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Assuming cluster numbers rank customer quality\",\n",
    "      \"B\": \"Treating every cluster as a known target label\",\n",
    "      \"C\": \"Domain judgment\",\n",
    "      \"D\": \"Ignoring what the features represent\"\n",
    "    }\n",
    "  },\n",
    "  {\n",
    "    \"format\": \"true_false\",\n",
    "    \"prompt\": \"True or false: A cluster labeled 2 is inherently better or more valuable than a cluster labeled 1.\",\n",
    "    \"concepts\": [\n",
    "      \"Cluster\",\n",
    "      \"Segmentation\"\n",
    "    ],\n",
    "    \"explanation\": \"False. Cluster numbers are identifiers, not rankings of value or quality. Interpretation comes from the group profiles and domain context, rather than the magnitude of the assigned label.\",\n",
    "    \"retry_hint\": \"Distinguish a group identifier from a measured or judged ranking.\",\n",
    "    \"id\": \"q10\",\n",
    "    \"cognitive_level\": \"connection\",\n",
    "    \"reading\": \"../1503-interpreting-clusters.html\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"True\",\n",
    "      \"B\": \"False\"\n",
    "    }\n",
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    "\n",
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    "    \"id\": \"q1\",\n",
    "    \"prompt\": \"Which term matches this explanation? Grouping observations based on similarity.\",\n",
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    "    \"concepts\": [\n",
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    "    ],\n",
    "    \"explanation\": \"Cluster: A group of observations that are similar to each other. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
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    "    \"id\": \"q3\",\n",
    "    \"prompt\": \"Which term matches this explanation? The center point of a k-means cluster.\",\n",
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    "      \"A\": \"Clustering\",\n",
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    "      \"C\": \"Cluster\",\n",
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    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Centroid\"\n",
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    "    \"explanation\": \"Centroid: The center point of a k-means cluster. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q4\",\n",
    "    \"prompt\": \"Which term matches this explanation? A rule for measuring how far observations are apart.\",\n",
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    "      \"A\": \"Clustering\",\n",
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    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Distance metric\"\n",
    "    ],\n",
    "    \"explanation\": \"Distance metric: A rule for measuring how far observations are apart. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q5\",\n",
    "    \"prompt\": \"Which term matches this explanation? Transforming variables so their scales are comparable.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Feature scaling\",\n",
    "      \"B\": \"Clustering\",\n",
    "      \"C\": \"Unsupervised learning\",\n",
    "      \"D\": \"Cluster\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Feature scaling\"\n",
    "    ],\n",
    "    \"explanation\": \"Feature scaling: Transforming variables so their scales are comparable. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q6\",\n",
    "    \"prompt\": \"Which term matches this explanation? How spread out points are inside a cluster.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Clustering\",\n",
    "      \"B\": \"Unsupervised learning\",\n",
    "      \"C\": \"Within-cluster variation\",\n",
    "      \"D\": \"Cluster\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Within-cluster variation\"\n",
    "    ],\n",
    "    \"explanation\": \"Within-cluster variation: How spread out points are inside a cluster. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q7\",\n",
    "    \"prompt\": \"Which term matches this explanation? A heuristic for choosing k by inspecting improvement as k increases.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Elbow method\",\n",
    "      \"B\": \"Unsupervised learning\",\n",
    "      \"C\": \"Clustering\",\n",
    "      \"D\": \"Cluster\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Elbow method\"\n",
    "    ],\n",
    "    \"explanation\": \"Elbow method: A heuristic for choosing k by inspecting improvement as k increases. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q8\",\n",
    "    \"prompt\": \"Which term matches this explanation? The number of features used to represent observations.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Clustering\",\n",
    "      \"B\": \"Unsupervised learning\",\n",
    "      \"C\": \"Dimensionality\",\n",
    "      \"D\": \"Cluster\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Dimensionality\"\n",
    "    ],\n",
    "    \"explanation\": \"Dimensionality: The number of features used to represent observations. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q9\",\n",
    "    \"prompt\": \"Which term matches this explanation? How easily cluster results can be explained.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Unsupervised learning\",\n",
    "      \"B\": \"Clustering\",\n",
    "      \"C\": \"Interpretability\",\n",
    "      \"D\": \"Cluster\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Interpretability\"\n",
    "    ],\n",
    "    \"explanation\": \"Interpretability: How easily cluster results can be explained. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  },\n",
    "  {\n",
    "    \"id\": \"q10\",\n",
    "    \"prompt\": \"Which term matches this explanation? A variable that adds distraction rather than useful grouping information.\",\n",
    "    \"choices\": {\n",
    "      \"A\": \"Clustering\",\n",
    "      \"B\": \"Noisy feature\",\n",
    "      \"C\": \"Unsupervised learning\",\n",
    "      \"D\": \"Cluster\"\n",
    "    },\n",
    "    \"format\": \"multiple_choice\",\n",
    "    \"cognitive_level\": \"recognition\",\n",
    "    \"concepts\": [\n",
    "      \"Noisy feature\"\n",
    "    ],\n",
    "    \"explanation\": \"Noisy feature: A variable that adds distraction rather than useful grouping information. This is the glossary meaning used by this original question.\",\n",
    "    \"retry_hint\": \"Compare the related terms in the assigned chapter glossary; identify what the description refers to.\",\n",
    "    \"reading\": \"../1500-clustering.html\"\n",
    "  }\n",
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    "  }\n",
    "\n",
    "  function loadSessionIdentity(identity, actions, submit, result) {\n",
    "    submit.disabled = true;\n",
    "    actions.classList.add('is-locked');\n",
    "    result.textContent = 'Sign in from the account menu to submit this assignment.';\n",
    "\n",
    "    return fetch('/api/v1/session.php', { credentials: 'same-origin' })\n",
    "      .then(function (response) { return response.ok ? response.json() : null; })\n",
    "      .then(function (payload) {\n",
    "        if (!payload || !payload.authenticated || !payload.identity) return identity;\n",
    "        identity.canvas_user_id = payload.identity.canvas_user_id || identity.canvas_user_id || '';\n",
    "        identity.student_identifier = payload.identity.student_identifier || identity.student_identifier || '';\n",
    "        submit.disabled = false;\n",
    "        actions.classList.remove('is-locked');\n",
    "        result.textContent = payload.identity.display_name ? 'Signed in as ' + payload.identity.display_name + '.' : 'Signed in.';\n",
    "        return identity;\n",
    "      })\n",
    "      .catch(function () { return identity; });\n",
    "  }\n",
    "\n",
    "  function renderQuestions(container) {\n",
    "    container.textContent = '';\n",
    "    questions.forEach(function (question, index) {\n",
    "      var card = document.createElement('div');\n",
    "      card.className = 'ch15-preview-question';\n",
    "      card.dataset.question = question.id;\n",
    "\n",
    "      var prompt = document.createElement('p');\n",
    "      prompt.appendChild(text((index + 1) + '. ' + question.prompt));\n",
    "      card.appendChild(prompt);\n",
    "\n",
    "      (attemptState ? attemptState.orders[question.id] : Object.keys(question.choices)).forEach(function (letter, position) {\n",
    "        var label = document.createElement('label');\n",
    "        var input = document.createElement('input');\n",
    "        input.type = 'radio';\n",
    "        input.name = question.id;\n",
    "        input.value = letter;\n",
    "        input.checked = !!(attemptState && attemptState.answers[question.id] === letter);\n",
    "        label.appendChild(input);\n",
    "        label.appendChild(text(String.fromCharCode(65 + position) + '. ' + question.choices[letter]));\n",
    "        card.appendChild(label);\n",
    "      });\n",
    "\n",
    "      var feedback = document.createElement('div');\n",
    "      feedback.className = 'ch15-preview-feedback';\n",
    "      feedback.setAttribute('aria-live', 'polite');\n",
    "      card.appendChild(feedback);\n",
    "      container.appendChild(card);\n",
    "    });\n",
    "  }\n",
    "\n",
    "  function collectAnswers(quiz) {\n",
    "    var answers = {};\n",
    "    questions.forEach(function (question) {\n",
    "      var selected = quiz.querySelector('input[name=' + question.id + ']:checked');\n",
    "      answers[question.id] = selected ? selected.value : '';\n",
    "    });\n",
    "    // Press stores this marker with the submitted answers; it is not a scored question.\n",
    "    answers.__question_set = attemptState ? attemptState.version : questionSetVersion;\n",
    "    if (attemptState) answers.preview_attempt = attemptState.token;\n",
    "    return answers;\n",
    "  }\n",
    "\n",
    "  function loadFeedbackPolicy() {\n",
    "    // Use the existing server release setting; a network failure must not unlock answers.\n",
    "    return fetch('/api/v1/assignment-settings.php?assignment_id=' + encodeURIComponent(quizId), {\n",
    "      credentials: 'same-origin'\n",
    "    })\n",
    "      .then(function (response) { return response.ok ? response.json() : null; })\n",
    "      .then(function (payload) {\n",
    "        answersUnlocked = !!(payload && payload.ok && payload.answers_unlocked === true);\n",
    "      })\n",
    "      .catch(function () { answersUnlocked = false; });\n",
    "  }\n",
    "\n",
    "  function applyFeedback(quiz, feedback) {\n",
    "    questions.forEach(function (question) {\n",
    "      var card = quiz.querySelector('[data-question=' + question.id + ']');\n",
    "      var message = card.querySelector('.ch15-preview-feedback');\n",
    "      var item = feedback[question.id];\n",
    "      message.className = 'ch15-preview-feedback';\n",
    "      var status = (!item || !item.submitted) ? 'No answer submitted.' :\n",
    "        (item.correct ? 'Correct.' : 'Review and try again.');\n",
    "      var guidance = answersUnlocked ? question.explanation : question.retry_hint;\n",
    "      message.textContent = status + ' ' + guidance;\n",
    "      var reading = document.createElement('a');\n",
    "      reading.href = question.reading || \"../1500-clustering.html\";\n",
    "      reading.appendChild(text('Review this concept'));\n",
    "      message.appendChild(text(' '));\n",
    "      message.appendChild(reading);\n",
    "      message.classList.add(item && item.correct ? 'correct' : 'incorrect');\n",
    "    });\n",
    "  }\n",
    "\n",
    "  function initLegacyPreviewQuiz() {\n",
    "    var quiz = document.getElementById('ch15-preview-quiz');\n",
    "    if (!quiz || quiz.dataset.ready === 'true') return;\n",
    "    quiz.dataset.ready = 'true';\n",
    "\n",
    "    var identity = getParams();\n",
    "    var questionsContainer = document.getElementById('ch15-preview-questions');\n",
    "    var result = document.getElementById('ch15-preview-result');\n",
    "    var submit = document.getElementById('ch15-preview-submit');\n",
    "    var actions = quiz.querySelector('.ch15-preview-actions');\n",
    "    var reset = document.getElementById('ch15-preview-reset');\n",
    "\n",
    "    renderQuestions(questionsContainer);\n",
    "    loadSessionIdentity(identity, actions, submit, result);\n",
    "\n",
    "    submit.addEventListener('click', function () {\n",
    "      var answers = collectAnswers(quiz);\n",
    "      submit.disabled = true;\n",
    "      result.textContent = 'Submitting...';\n",
    "\n",
    "      fetch('/api/v1/quiz-attempts.php', {\n",
    "        method: 'POST',\n",
    "        headers: { 'Content-Type': 'application/json' },\n",
    "        credentials: 'same-origin',\n",
    "        body: JSON.stringify({\n",
    "          quiz_id: quizId,\n",
    "          question_set_version: questionSetVersion,\n",
    "          answers: answers,\n",
    "          student_identifier: identity.student_identifier || identity.canvas_user_id || '',\n",
    "          canvas_course_id: identity.canvas_course_id,\n",
    "          canvas_assignment_id: identity.canvas_assignment_id,\n",
    "          canvas_user_id: identity.canvas_user_id\n",
    "        })\n",
    "      })\n",
    "        .then(function (response) {\n",
    "          return response.text().then(function (text) {\n",
    "            var payload = null;\n",
    "            try {\n",
    "              payload = text ? JSON.parse(text) : null;\n",
    "            } catch (error) {\n",
    "              throw new Error('Server returned a non-JSON response (HTTP ' + response.status + '): ' + text.slice(0, 160));\n",
    "            }\n",
    "            if (!payload) {\n",
    "              throw new Error('Server returned an empty response (HTTP ' + response.status + '). Check that PHP is enabled for /api/v1/quiz-attempts.php.');\n",
    "            }\n",
    "            if (!response.ok || !payload.ok) {\n",
    "              throw new Error(payload.message || payload.error || 'Submission failed.');\n",
    "            }\n",
    "            return payload;\n",
    "          });\n",
    "        })\n",
    "        .then(function (payload) {\n",
    "          var best = (payload.best_score === null || typeof payload.best_score === 'undefined') ? payload.score : payload.best_score;\n",
    "          var attempt = (payload.attempt_count === null || typeof payload.attempt_count === 'undefined') ? '' : ' Attempt ' + payload.attempt_count + '.';\n",
    "          return loadFeedbackPolicy().then(function () {\n",
    "            applyFeedback(quiz, payload.feedback || {});\n",
    "            result.textContent = 'Submission saved.' + attempt + ' Score: ' + payload.score + ' / ' + payload.max_score + '. Best score: ' + best + ' / ' + payload.max_score + '. Canvas sync: ' + payload.canvas_sync_status + '.';\n",
    "            if (!answersUnlocked) result.textContent += ' Full explanations are available when answers are released.';\n",
    "          });\n",
    "        })\n",
    "        .catch(function (error) {\n",
    "          result.textContent = 'Could not save this attempt: ' + error.message;\n",
    "        })\n",
    "        .finally(function () {\n",
    "          submit.disabled = false;\n",
    "        });\n",
    "    });\n",
    "\n",
    "    reset.addEventListener('click', function () {\n",
    "      quiz.querySelectorAll('input[type=radio]').forEach(function (input) {\n",
    "        input.checked = false;\n",
    "      });\n",
    "      quiz.querySelectorAll('.ch15-preview-feedback').forEach(function (feedback) {\n",
    "        feedback.className = 'ch15-preview-feedback';\n",
    "        feedback.textContent = '';\n",
    "      });\n",
    "      result.textContent = '';\n",
    "    });\n",
    "  }\n",
    "\n",
    "\n",
    "  function initPreviewQuiz() {\n",
    "    // The legacy PHP host retains its existing fixed-order delivery until it migrates to Press.\n",
    "    if (!/(^|\\.)thinkpress\\.org$/.test(window.location.hostname) &&\n",
    "        !['localhost', '127.0.0.1'].includes(window.location.hostname)) return initLegacyPreviewQuiz();\n",
    "    var quiz = document.getElementById('ch15-preview-quiz');\n",
    "    if (!quiz || quiz.dataset.ready === 'true') return;\n",
    "    quiz.dataset.ready = 'true';\n",
    "\n",
    "    var identity = getParams();\n",
    "    var questionsContainer = document.getElementById('ch15-preview-questions');\n",
    "    var result = document.getElementById('ch15-preview-result');\n",
    "    var submit = document.getElementById('ch15-preview-submit');\n",
    "    var actions = quiz.querySelector('.ch15-preview-actions');\n",
    "    var reset = document.getElementById('ch15-preview-reset');\n",
    "\n",
    "    // Press owns this quiz's draft and option order; the generic runner must not restore older inputs over it.\n",
    "    quiz.classList.add('press-preview-managed');\n",
    "    var next = document.createElement('button');\n",
    "    next.type = 'button';\n",
    "    next.textContent = 'Start a new attempt';\n",
    "    next.hidden = true;\n",
    "    actions.appendChild(next);\n",
    "\n",
    "    function lockQuestions(locked) {\n",
    "      quiz.querySelectorAll('input[type=radio]').forEach(function (input) { input.disabled = locked; });\n",
    "      reset.disabled = locked;\n",
    "    }\n",
    "    function showState(payload) {\n",
    "      questions = attemptState.questions;\n",
    "      renderQuestions(questionsContainer);\n",
    "      lockQuestions(payload.completed);\n",
    "      submit.disabled = payload.completed;\n",
    "      next.hidden = !payload.completed;\n",
    "      if (!payload.completed) result.textContent = '';\n",
    "      if (attemptState.preserved_draft && !payload.completed) {\n",
    "        result.textContent = 'Resumed your saved answers with their original option order.';\n",
    "      }\n",
    "      if (payload.result) {\n",
    "        return loadFeedbackPolicy().then(function () {\n",
    "          applyFeedback(quiz, payload.result.feedback || {});\n",
    "          result.textContent = 'Saved attempt. Score: ' + payload.result.score + ' / ' + payload.result.max_score +\n",
    "            '. Best score: ' + payload.result.best_score + ' / ' + payload.result.max_score + '.';\n",
    "          if (!answersUnlocked) result.textContent += ' Full explanations are available when answers are released.';\n",
    "        });\n",
    "      }\n",
    "      return Promise.resolve();\n",
    "    }\n",
    "    renderQuestions(questionsContainer);\n",
    "    lockQuestions(true);\n",
    "    loadSessionIdentity(identity, actions, submit, result).then(function () {\n",
    "      if (submit.disabled) return;\n",
    "      submit.disabled = true;\n",
    "      result.textContent = 'Resuming your Preview...';\n",
    "      return stateRequest('resume').then(showState).catch(function (error) {\n",
    "        submit.disabled = true;\n",
    "        result.textContent = 'Could not resume this Preview: ' + error.message + ' Reload to retry.';\n",
    "      });\n",
    "    });\n",
    "\n",
    "    quiz.addEventListener('change', function (event) {\n",
    "      if (!event.target || event.target.type !== 'radio' || !attemptState) return;\n",
    "      saveAnswers(quiz).catch(function (error) { result.textContent = 'Answers not saved: ' + error.message; });\n",
    "    });\n",
    "\n",
    "    submit.addEventListener('click', async function () {\n",
    "      submit.disabled = true;\n",
    "      lockQuestions(true);\n",
    "      result.textContent = 'Submitting...';\n",
    "      try {\n",
    "        await saveAnswers(quiz);\n",
    "        var response = await fetch('/api/v1/quiz-attempts.php', {\n",
    "          method: 'POST', headers: { 'Content-Type': 'application/json' }, credentials: 'same-origin',\n",
    "          body: JSON.stringify({ quiz_id: quizId, answers: collectAnswers(quiz),\n",
    "            question_set_version: attemptState.version,\n",
    "            student_identifier: identity.student_identifier || identity.canvas_user_id || '',\n",
    "            canvas_course_id: identity.canvas_course_id, canvas_assignment_id: identity.canvas_assignment_id,\n",
    "            canvas_user_id: identity.canvas_user_id })\n",
    "        });\n",
    "        var payload = await response.json();\n",
    "        if (!response.ok || !payload.ok) throw new Error(payload.message || payload.error || 'Submission failed.');\n",
    "        await loadFeedbackPolicy();\n",
    "        applyFeedback(quiz, payload.feedback || {});\n",
    "        result.textContent = 'Submission saved. Attempt ' + payload.attempt_count + '. Score: ' + payload.score +\n",
    "          ' / ' + payload.max_score + '. Best score: ' + payload.best_score + ' / ' + payload.max_score + '.';\n",
    "        if (!answersUnlocked) result.textContent += ' Full explanations are available when answers are released.';\n",
    "        next.hidden = false;\n",
    "      } catch (error) {\n",
    "        result.textContent = 'Could not save this attempt: ' + error.message;\n",
    "        submit.disabled = false;\n",
    "        lockQuestions(false);\n",
    "      }\n",
    "    });\n",
    "\n",
    "    reset.addEventListener('click', function () {\n",
    "      submit.disabled = true;\n",
    "      stateQueue = stateQueue.catch(function () {}).then(function () { return stateRequest('clear'); });\n",
    "      stateQueue.then(function (payload) { result.textContent = ''; return showState(payload); })\n",
    "        .catch(function (error) { result.textContent = error.message; submit.disabled = false; });\n",
    "    });\n",
    "    next.addEventListener('click', function () {\n",
    "      next.disabled = true;\n",
    "      stateRequest('next').then(function (payload) { result.textContent = ''; return showState(payload); })\n",
    "        .catch(function (error) { result.textContent = error.message; })\n",
    "        .finally(function () { next.disabled = false; });\n",
    "    });\n",
    "  }\n",
    "\n",
    "  if (document.readyState === 'loading') {\n",
    "    document.addEventListener('DOMContentLoaded', initPreviewQuiz);\n",
    "  } else {\n",
    "    initPreviewQuiz();\n",
    "  }\n",
    "})();\n",
    "</script>"
   ]
  }
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