{
  "format": "dataset-manifest/1",
  "slug": "google-classroom",
  "version": 1,
  "seed": "google-classroom:1",
  "spec": {
    "format": "dataset/1",
    "slug": "google-classroom",
    "name": "Hospitality Classroom Engagement",
    "tagline": "Student engagement metrics from a hospitality training program, including coursework participation and feedback.",
    "description": "Students actively participate in various hospitality training courses, honing their skills in customer service, cooking, and event management. Instructors design engaging coursework that encourages student involvement and tracks progress through measurable indicators. Each engagement event captures a moment of participation, providing insights into how students interact with the material and with one another. As students navigate through assignments, they contribute to discussions, submit their work, and receive feedback, creating a dynamic learning environment that adapts to their needs.\n\nThe engagement_events table records each instance of student participation, with columns detailing the student ID, event type, timestamp, and assignment related to the engagement. This structure allows for a granular view of how often students are involved, the types of assignments they prefer, and how engagement levels fluctuate over time. By joining this table with student profiles or course descriptions, further analysis can be performed to draw correlations between engagement levels and student performance or course success.\n\nThis data is particularly useful for addressing questions such as: Which assignments receive the most attention? Are there patterns in engagement related to specific topics? How does student participation vary over the duration of the course? Practicing with this dataset can enhance skills in data analysis, pattern recognition, and drawing meaningful conclusions from educational data.\n\nIt's important to note that the data within this dataset is synthetic, created to simulate real-world participation in a hospitality training environment. This allows for the exploration of various scenarios without the complexities of actual student data, making it an excellent resource for developers looking to practice on educational engagement metrics.",
    "domain": "hospitality",
    "shape": "event-log",
    "useCases": [
      "analytics-demo",
      "etl-pipelines"
    ],
    "keywords": [
      "hospitality",
      "student engagement",
      "coursework",
      "assignments",
      "feedback",
      "analytics"
    ],
    "locale": "en",
    "license": "CC0-1.0",
    "version": 1,
    "tables": {
      "engagement_events": {
        "description": "Each row represents an engagement event by a student in a hospitality training course, linking to different activities like submissions and announcements. This helps track participation and feedback over time.",
        "rows": 500,
        "columns": {
          "id": {
            "kind": "pk",
            "description": "Unique identifier for each engagement event."
          },
          "student_id": {
            "kind": "uuid",
            "description": "Unique identifier for the student involved in the engagement."
          },
          "event_type": {
            "kind": "enum",
            "values": [
              "submission",
              "announcement",
              "feedback"
            ],
            "description": "Type of engagement event."
          },
          "course_id": {
            "kind": "uuid",
            "description": "Unique identifier for the course related to the engagement."
          },
          "event_timestamp": {
            "kind": "datetime",
            "from": "2023-01-01",
            "to": "2023-12-31",
            "description": "Timestamp of when the engagement event occurred.",
            "dayProfile": "waking"
          },
          "assignment_id": {
            "kind": "uuid",
            "nullable": true,
            "description": "Unique identifier for the assignment, if applicable."
          },
          "comments": {
            "kind": "words",
            "min": 1,
            "max": 50,
            "description": "Comments or feedback provided by the student during the engagement."
          },
          "grade": {
            "kind": "decimal",
            "min": 0,
            "max": 100,
            "description": "Grade received for the assignment, if applicable."
          }
        }
      }
    },
    "structure": "single-table",
    "traits": [
      "timestamped",
      "nullable",
      "high-cardinality"
    ],
    "analysisQuestions": [
      "What are the most common types of engagement events among students?",
      "How does student engagement vary across different courses?",
      "What trends can be identified in student feedback over time?",
      "Which assignments have the highest and lowest engagement rates?",
      "Are there specific periods when student engagement peaks or declines?"
    ],
    "suggestedQueries": [
      {
        "title": "Count of Engagement Events by Type",
        "sql": "SELECT event_type, COUNT(*) FROM engagement_events GROUP BY event_type;",
        "dialect": "postgres"
      },
      {
        "title": "Average Grade by Course",
        "sql": "SELECT course_id, AVG(grade) FROM engagement_events WHERE grade IS NOT NULL GROUP BY course_id;",
        "dialect": "postgres"
      },
      {
        "title": "Engagement Events Over Time",
        "sql": "SELECT DATE_TRUNC('month', event_timestamp) AS month, COUNT(*) FROM engagement_events GROUP BY month ORDER BY month;",
        "dialect": "postgres"
      },
      {
        "title": "Comments for Submissions",
        "sql": "SELECT comments FROM engagement_events WHERE event_type = 'submission' AND comments IS NOT NULL;",
        "dialect": "postgres"
      }
    ],
    "usageScenarios": [
      {
        "title": "Course Instructors Analyzing Engagement",
        "body": "Instructors can utilize this dataset to analyze student engagement patterns within their courses. By examining the types of engagement events and the timing of submissions or feedback, they can identify which aspects of their course materials resonate well with students and which may need adjustments."
      },
      {
        "title": "Administrative Staff Reporting on Student Performance",
        "body": "Administrative staff can leverage the data to generate reports on student performance and engagement. By aggregating the information on grades and participation rates, they can provide insights into overall student success and make data-driven decisions to improve course offerings."
      },
      {
        "title": "Data Analysts Conducting Educational Research",
        "body": "Data analysts can use the dataset to conduct research on educational engagement in hospitality training. They can explore correlations between engagement activities and student performance, contributing to the broader field of educational studies focused on improving student outcomes."
      }
    ]
  },
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  },
  "stats": {
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          "min": "2023-01-01 08:54:37",
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        "grade": {
          "nulls": 0,
          "distinct": 485,
          "min": 0.04,
          "max": 99.92
        }
      }
    }
  },
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