Datasets:

robworks-software
/

k12-digital-learning-platforms

Error code:   StreamingRowsError
Exception:    CastError
Message:      Couldn't cast
year: int32
quarter: string
platform_name: string
market_share_percentage: float
total_institutions: int32
total_users: int64
growth_rate_annual: float
geographic_scope: string
data_source: string
-- schema metadata --
huggingface: '{"info": {"features": {"year": {"dtype": "int32", "_type": ' + 472
to
{'platform_name': Value('string'), 'platform_type': Value('string'), 'subject_focus': List(Value('string')), 'total_registered_users': Value('int64'), 'active_users_monthly': Value('int64'), 'accuracy_rate_percentage': Value('float32'), 'user_satisfaction_score': Value('float32'), 'districts_using': Value('int32'), 'teachers_trained': Value('int32')}
because column names don't match
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/utils.py", line 99, in get_rows_or_raise
                  return get_rows(
                File "/src/libs/libcommon/src/libcommon/utils.py", line 272, in decorator
                  return func(*args, **kwargs)
                File "/src/services/worker/src/worker/utils.py", line 77, in get_rows
                  rows_plus_one = list(itertools.islice(ds, rows_max_number + 1))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2361, in __iter__
                  for key, example in ex_iterable:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1882, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1905, in _iter_arrow
                  for key, pa_table in self.ex_iterable._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 499, in _iter_arrow
                  for key, pa_table in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 346, in _iter_arrow
                  for key, pa_table in self.generate_tables_fn(**gen_kwags):
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 106, in _generate_tables
                  yield f"{file_idx}_{batch_idx}", self._cast_table(pa_table)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/packaged_modules/parquet/parquet.py", line 73, in _cast_table
                  pa_table = table_cast(pa_table, self.info.features.arrow_schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2272, in table_cast
                  return cast_table_to_schema(table, schema)
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/table.py", line 2218, in cast_table_to_schema
                  raise CastError(
              datasets.table.CastError: Couldn't cast
              year: int32
              quarter: string
              platform_name: string
              market_share_percentage: float
              total_institutions: int32
              total_users: int64
              growth_rate_annual: float
              geographic_scope: string
              data_source: string
              -- schema metadata --
              huggingface: '{"info": {"features": {"year": {"dtype": "int32", "_type": ' + 472
              to
              {'platform_name': Value('string'), 'platform_type': Value('string'), 'subject_focus': List(Value('string')), 'total_registered_users': Value('int64'), 'active_users_monthly': Value('int64'), 'accuracy_rate_percentage': Value('float32'), 'user_satisfaction_score': Value('float32'), 'districts_using': Value('int32'), 'teachers_trained': Value('int32')}
              because column names don't match

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K-12 Digital Learning Platforms Usage Dataset

Dataset Description

This comprehensive dataset provides detailed information about digital learning platform usage, effectiveness, and trends in K-12 education. It covers Learning Management Systems (LMS), educational applications, AI tutoring systems, screen time impacts, and educational technology tools.

Dataset Summary

Total Records: 4
Platforms Tracked: 1
Research Studies: 1
Market Data Points: 1
Geographic Scope: United States and Canada
Time Period: 2020-2025

Dataset Structure

Data Sources

LearnPlatform by Instructure reports
Common Sense Media research studies
NCES (National Center for Education Statistics)
Academic research publications
Platform vendor statistics and reports
Market research organizations

Usage Examples

Research Applications

Educational technology effectiveness studies
Policy development and decision-making
Academic research on digital learning trends
Market analysis and competitive intelligence

Practical Applications

District technology planning and procurement
Platform evaluation and selection
Teacher training and professional development
Budget planning and cost analysis

Data Quality

Validation

Multi-source cross-validation
Automated quality checks
Expert review and curation
Regular accuracy audits

Limitations

Self-reported data limitations in some studies
Varying data collection methodologies across sources
Geographic bias toward North American data
Temporal lag in some research studies

Citation

@dataset{k12_digital_platforms_2025,
  title={K-12 Digital Learning Platforms Usage Dataset},
  author={Robworks Software},
  organization={https://robworks.info},
  year={2025},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/robworks-software/k12-digital-learning-platforms}
}