Maintainer	bastiaan.heeren@ou.nl
Stability	provisional
Portability	portable (depends on ghc)
Safe Haskell	None
Language	Haskell98

Database.HumanAssessment

Description

Access to human assessments of the databases.

This module reads spreadsheets containing human assessments of the data we have collected. This will enable us to compare the data, and use human-collected evidence to feed the Bayesian networks.

Synopsis

data Tally = Tally {
- matchState :: [Match]
- matchAbsence :: [Match]
- mismatchState :: [Match]
- expectedPresence :: [Match]
- expectedAbsence :: [Match]
}
data Match = Match {
- locStudent :: StudentID
- locTask :: TaskID
- locNode :: NodeID
- expectation :: Maybe String
- observation :: Maybe String
}
prettyMatches :: [Match] -> Doc
summarise :: Foldable t => t Tally -> Tally
summariseTasks :: Map (TaskID, NodeID) Tally -> Map TaskID Tally
score :: (Tally -> Int) -> (Tally -> Int) -> Tally -> Double
tally :: FilePath -> FilePath -> IO (Map (TaskID, NodeID) Tally)
tally' :: Xlsx -> Map (StudentID, TaskID) Evidence -> IO (Map (TaskID, NodeID) Tally)
getSpreadsheet :: FilePath -> IO Xlsx
getEvidence :: Xlsx -> Map (StudentID, TaskID) Evidence
getHumanMachineFiles :: FilePath -> FilePath -> IO [(PilotID, FilePath, FilePath)]
readEvidence :: FilePath -> IO (Map (StudentID, TaskID) Evidence)

Documentation

data Tally Source #

Group matches together groupMatches :: [Match] -> [((StudentID,TaskID), Match)] groupMatches = orderBy (locStudent &&& locTask)

Counter for the number of times we encounter agreements and disagreements between the human and the machine assessment.

Constructors

Tally
Fields matchState :: [Match] Human & machine assessment match on state matchAbsence :: [Match] Neither human nor machine set a state on the node mismatchState :: [Match] Human & machine set a state, but not the same expectedPresence :: [Match] Machine does not set a state but human does expectedAbsence :: [Match] Human does not set a state but machine does

Instances

Semigroup Tally Source #
Instance details Defined in Database.HumanAssessment Methods (<>) :: Tally -> Tally -> Tally # sconcat :: NonEmpty Tally -> Tally # stimes :: Integral b => b -> Tally -> Tally #
Monoid Tally Source #
Instance details Defined in Database.HumanAssessment Methods mempty :: Tally # mappend :: Tally -> Tally -> Tally # mconcat :: [Tally] -> Tally #
Pretty Tally Source #
Instance details Defined in Database.HumanAssessment Methods pretty :: Tally -> Doc # prettyList :: [Tally] -> Doc #

data Match Source #

Where did a match or mismatch occur?

Constructors

Match
Fields locStudent :: StudentID locTask :: TaskID locNode :: NodeID expectation :: Maybe String Human assessment observation :: Maybe String Machine assessment

Instances

Pretty Match Source #
Instance details Defined in Database.HumanAssessment Methods pretty :: Match -> Doc # prettyList :: [Match] -> Doc #

prettyMatches :: [Match] -> Doc Source #

summarise :: Foldable t => t Tally -> Tally Source #

Combine multiple tallies.

summariseTasks :: Map (TaskID, NodeID) Tally -> Map TaskID Tally Source #

Summarise the tallies per task by combining the tallies for each node.

score :: (Tally -> Int) -> (Tally -> Int) -> Tally -> Double Source #

Convert tally fields to a corresponding score.

tally :: FilePath -> FilePath -> IO (Map (TaskID, NodeID) Tally) Source #

tally' :: Xlsx -> Map (StudentID, TaskID) Evidence -> IO (Map (TaskID, NodeID) Tally) Source #

Get the tallies for every task/node combination, based on a spreadsheet file with expected, human-assessed values and a database file with observed, IDEAS-assessed values.

getSpreadsheet :: FilePath -> IO Xlsx Source #

getEvidence :: Xlsx -> Map (StudentID, TaskID) Evidence Source #

Get expected evidence from a spreadsheet.

getHumanMachineFiles :: FilePath -> FilePath -> IO [(PilotID, FilePath, FilePath)] Source #

Obtain a list of pilots and associated spreadsheet + database files.

readEvidence :: FilePath -> IO (Map (StudentID, TaskID) Evidence) Source #

Get evidence from an Excel file.