if (!requireNamespace("catR", quietly = TRUE)) install.packages("catR")
if (!requireNamespace("readxl", quietly = TRUE)) install.packages("readxl")
# ==========================================
# Computerized Assessment Tool (catR, 3PL)
# Files expected in same folder:
#   - R_Assessment_Tool.R
#   - Survey_ItemBank_for_R.xlsx
# ==========================================
library(catR)
library(readxl)

# ---- Load item bank ----
excel_path <- "C:/R/Survey_ItemBank_for_R.xlsx"
ib <- read_excel(excel_path)
# Expected columns in Excel:
# Question_ID | Item_Text | Answe3r_Options | Correct_Answer | a | b | c
# Build catR item parameter matrix a, b, c, D
a <- as.numeric(ib$a)
b <- as.numeric(ib$b)
c <- as.numeric(ib$c)
itemBank <- cbind(a, b, c, rep(1, length(a)))   # D = 1

# ---- Config ----
max_items <- 10L           # fixed-length assessment (can be changed)
theta_current <- 0         # initial theta guess
administered <- integer(0) # indices of items asked
responses   <- integer(0)  # 1 correct, 0 incorrect
# Keep track of only scored (objective) items for theta estimation
scored_admin <- integer(0)  # indices of scored items
scored_resp  <- integer(0)  # responses (1/0) for scored items
log_rows <- list()
cat("\n===== Adaptive Assessment (3PL; ML; length =", max_items, ") =====\n")
cat("Answer by typing the OPTION NUMBER (1, 2, 3, ...) and press Enter.\n")

# ---- Ask one item ----
ask_item <- function(i_row) {
qid   <- if ("Question_ID" %in% names(ib)) ib$Question_ID[i_row] else i_row
qtext <- ib$Item_Text[i_row]
opts  <- ib$Answer_Options[i_row]
cat("\n------------------------------------------------------------\n")
cat(sprintf("Question %s\n", as.character(qid)))
cat(paste0(qtext, "\n"))
cat("Options:\n")
cat(paste0(opts, "\n"))  # e.g., "1 = ..., 2 = ..., 3 = ..."
repeat {
ans <- readline(prompt = "Your answer (option number): ")
if (nzchar(ans) && grepl("^[0-9]+$", ans)) return(as.integer(ans))
cat("Please enter a number like 1, 2, 3 ...\n")
}
}

# ---- Adaptive loop ----
while (length(administered) < max_items) {
# select next item (MFI)
sel <- nextItem(itemBank, theta = theta_current, out = administered, criterion = "MFI")
i <- sel$item
# ask user
choice <- ask_item(i)
# correct option (must be the option number in Excel)
correct_option <- suppressWarnings(as.integer(ib$Correct_Answer[i]))
# If NA (opinion/Likert item), do not score it
if (is.na(correct_option)) {
is_correct <- NA_integer_
} else {
is_correct <- as.integer(identical(choice, correct_option))
# add to scored lists for theta estimation
scored_admin <- c(scored_admin, i)
scored_resp  <- c(scored_resp,  is_correct)
}
# record in main log (keep NA for opinion items)
administered <- c(administered, i)
responses    <- c(responses, ifelse(is.na(is_correct), NA_integer_, is_correct))
# re-estimate theta ONLY from scored items
if (length(scored_resp) > 0) {
theta_current <- thetaEst(
it     = itemBank[scored_admin, , drop = FALSE],
x      = scored_resp,
method = "ML",
D      = 1
)
}
# log
log_rows[[length(administered)]] <- data.frame(
step = length(administered),
question_index = i,
question_id = if ("Question_ID" %in% names(ib)) as.character(ib$Question_ID[i]) else as.character(i),
user_choice = choice,
correct_option = correct_option,
correct = is_correct,
scored = !is.na(is_correct),
theta_hat = as.numeric(theta_current)
)
cat(sprintf(
"→ Saved. Correct option = %s | Your answer = %s | Θ̂ (ML) = %.3f\n",
ifelse(is.na(correct_option), "NA", as.character(correct_option)),
as.character(choice),
as.numeric(theta_current)
))
# If opinion-based (no correct answer), show a clear note
if (is.na(correct_option)) {
cat("→ Opinion-based item: excluded from scoring.\n")
}
}

# ---- Finish ----
results <- do.call(rbind, log_rows)
write.csv(results, "assessment_log.csv", row.names = FALSE)
cat("\n===== Assessment finished =====\n")
cat(sprintf("Items administered: %d\n", nrow(results)))
cat(sprintf("Final ability estimate (Θ̂, ML, D=1): %.3f\n", results$theta_hat[nrow(results)]))
cat(sprintf("Total correct (scored): %d / %d\n",
sum(results$correct, na.rm = TRUE),
sum(!is.na(results$correct))))
cat('Log saved as "assessment_log.csv" in this folder.\n')