Pipe operator

Description

See magrittr::%>% for details.

Usage

lhs %>% rhs

Arguments

Value

The result of calling rhs(lhs).

Create a colored HTML span badge (UI helper)

Description

Generates a colored HTML badge for displaying values (like p-values or correlations) in the Shiny UI.

Usage

color_badge(v, type = c("generic", "p", "r"))

Arguments

Value

An htmltools::span() object.

Examples

if (interactive()) {
  # Example for difficulty (p)
  color_badge(0.5, "p")
  # Example for discrimination (r)
  color_badge(0.2, "r")
}

Generate translation keys for overall comments

Description

Creates a vector of translation keys based on average difficulty (ap) and discrimination (ar).

Usage

comment_overall_keys(ap, ar)

Arguments

Value

A character vector of translation keys.

Examples

comment_overall_keys(0.6, 0.35) # Medium, Keep
comment_overall_keys(0.2, 0.15) # Hard, Remove

Calculate the mode

Description

Finds the most frequent value (the mode) in a vector.

Usage

d_mode(x)

Arguments

Value

The mode of the vector. Returns NA if the vector is empty.

Examples

d_mode(c(1, 2, 2, 3, 3, 3, 4))
d_mode(c("a", "b", "a"))

Detect ID columns using regex

Description

Searches a vector of column names for common ID-related patterns.

Usage

detect_id_cols(cols)

Arguments

Value

A character vector of names that matched the ID pattern.

Examples

detect_id_cols(c("Ad", "Soyad", "ogrenci no", "Madde1", "StudentID"))

Generate label key for difficulty (p)

Description

Returns a specific translation key based on an item's difficulty value.

Usage

difficulty_label_key(p)

Arguments

Value

A character string (translation key).

Examples

difficulty_label_key(0.3) # Hard
difficulty_label_key(0.7) # Medium
difficulty_label_key(0.9) # Easy

Generate label key for discrimination (r)

Description

Returns a specific translation key based on an item's discrimination value.

Usage

discrimination_decision_key(r)

Arguments

Value

A character string (translation key).

Examples

discrimination_decision_key(0.15) # Remove
discrimination_decision_key(0.25) # Consider
discrimination_decision_key(0.4)  # Keep

Safely get quantile from 'psychometric' package

Description

Tries to get the default quant argument from psychometric::item.exam. Returns 0.27 if the package is not installed or an error occurs.

Usage

get_itemexam_quant()

Value

A numeric value for the quantile (default 0.27).

Examples

get_itemexam_quant()

Null-coalescing operator

Description

Returns a unless it is NULL; otherwise returns b.

Usage

a %||% b

Arguments

Value

a if not NULL, else b.

Load translation dictionary

Description

Finds ⁠<lang>.json⁠ under the installed package's ⁠i18n/⁠ folder and, if not found (during development), falls back to ⁠inst/i18n/<lang>.json⁠.

Usage

i18n_load(lang = "tr")

Arguments

Value

A named list (key -> string) parsed from the JSON file.

Examples

# Always-fast: locate the installed TR dictionary (empty string if not installed)
system.file("shinyapp", "i18n", "tr.json", package = "examly")

# Safe example that runs only if the file actually exists
p <- system.file("shinyapp", "i18n", "tr.json", package = "examly")
if (nzchar(p) && file.exists(p)) {
  d <- i18n_load("tr")
  i18n_t(d, "ui.title", "Baslik")
}

Translate a UI/message key

Description

Returns the value for key from a dictionary produced by i18n_load(). If the key is missing, returns default when provided, otherwise the key itself.

Usage

i18n_t(dict, key, default = NULL)

Arguments

Value

Character scalar.

Examples

# A quick, fully automatic check:
p <- system.file("shinyapp", "i18n", "en.json", package = "examly")
if (nzchar(p) && file.exists(p)) {
  d <- i18n_load("en")
  i18n_t(d, "buttons.download", "Download")
}

Check if a vector is scored 0/1

Description

Detects if a vector (after removing NAs) contains only 0 and 1.

Usage

is_scored_01(vec)

Arguments

Value

TRUE if the vector is 0/1 scored, FALSE otherwise.

Examples

is_scored_01(c(1, 0, 1, 0, NA))
is_scored_01(c(1, 0, 2, 0))
is_scored_01(c("A", "B", "C"))

Calculate KR-20 reliability coefficient

Description

Calculates the Kuder-Richardson 20 (KR-20) reliability coefficient for a data.frame or matrix of dichotomous (0/1) items.

Usage

kr20(m)

Arguments

Value

A numeric value for the KR-20 coefficient, or NA_real_ if calculation is not possible.

Examples

item_matrix <- data.frame(
  m1 = c(1, 1, 0, 1),
  m2 = c(1, 0, 1, 1),
  m3 = c(0, 1, 0, 0)
)
kr20(item_matrix)

Normalize Column Names

Description

A helper function that takes a mixed character vector or a single semi-colon/comma-separated string and returns a clean character vector of column names.

Usage

norm_cols(x)

Arguments

Value

A character vector of trimmed, non-empty column names.

Examples

norm_cols(" m1 , m2;m3")
norm_cols(c(" m1 ", "m2", "", " m3 "))

Normalize letter grades

Description

Cleans and validates a vector of characters, keeping only standard letter grades (A, B, C, D, E).

Usage

norm_letter(x)

Arguments

Value

A character vector of normalized grades (A-E) or NA.

Examples

norm_letter(c(" a ", "B", "c", "F", "d", NA))

Parse 1/0 coded data

Description

Validates that a vector contains only 1s, 0s, or NAs.

Usage

parse_lc_bin(x)

Arguments

Value

An integer vector (1, 0, or NA).

Examples

parse_lc_bin(c(1, 0, "1", "0", 2, "A", NA))

Parse raw continuous/Likert scores

Description

Cleans a vector of potential scores, converting to numeric and removing invalid or out-of-range values.

Usage

parse_lc_raw(x)

Arguments

Value

A numeric vector of cleaned scores.

Examples

parse_lc_raw(c("10", "5.5", "0", "-2", "ikiyüz", NA, "1000001"))

Score Multiple Choice items as 1/0

Description

Scores a Multiple Choice (A-E) response vector against a key.

Usage

parse_mc_bin(x, key)

Arguments

Value

An integer vector (1=correct, 0=wrong, NA=invalid).

Examples

parse_mc_bin(c("a", "B", "c", "F", " b "), key = "B")

Score True/False items as 1/0

Description

Scores a True/False (Doğru/Yanlış) response vector against a key.

Usage

parse_tf_bin(x, key)

Arguments

Value

An integer vector (1=correct, 0=wrong, NA=invalid).

Examples

parse_tf_bin(c("D", "Y", "DOGRU", "False", "Belki"), key = "D")

Point-biserial correlation for item analysis

Description

Calculates the correlation between a single item's score and the rest of the total score.

Usage

pbiserial_rest(item, rest)

Arguments

Value

The point-biserial correlation coefficient.

Examples

item1 <- c(1, 0, 1, 0, 1, 1)
rest_score <- c(10, 8, 12, 5, 9, 11)
pbiserial_rest(item1, rest_score)

Calculate q-index (1 - p)

Description

A simple helper to calculate the inverse of the p-value (difficulty index).

Usage

q_index(p)

Arguments

Value

A numeric value or vector (1 - p).

Examples

q_index(0.8)
q_index(c(0.2, 0.5, 0.7))

Launch examly Shiny application

Description

Launches the packaged Shiny app located in inst/shinyapp. If the app files are not found, a minimal placeholder app is launched instead.

Usage

run_app()

Details

This function is exported so users can run examly::run_app().

Value

Invisibly returns NULL. Called for its side effects.

Examples

system.file("shinyapp", package = "examly")
if(interactive()){
examly::run_app()
}

Student-level counts (Correct/Incorrect/Missing)

Description

Calculates the total number of correct, incorrect, and missing answers for each student (row).

Usage

student_counts(sc)

Arguments

Value

A tibble with columns Dogru, Yanlis, and Bos.

Examples

score_df <- data.frame(m1 = c(1, 0, 1), m2 = c(0, 1, NA), m3 = c(1, 1, 1))
student_counts(score_df)