{"app.R": "library(shiny)\nlibrary(bslib)\nlibrary(dplyr)\n\nsource(\"ui.R\")\nsource(\"server.R\")\n\nshinyApp(ui = ui, server = server)", "server.R": "library(magrittr)\nlibrary(dplyr)\nlibrary(shiny)\nlibrary(ggplot2)\n\n# Simulated data generation\ngenerate_sample_data <- function() {\n dates <- seq(as.Date('2023-01-01'), as.Date('2023-12-31'), by='days')\n data.frame(\n date = rep(dates, 4),\n course = rep(c(\"Mathematics\", \"Science\", \"English\", \"History\"), each = length(dates)),\n score = runif(length(dates) * 4, 60, 100),\n engagement = runif(length(dates) * 4, 0, 1)\n )\n}\n\nserver <- function(input, output, session) {\n # Reactive data\n sample_data <- reactive({\n generate_sample_data()\n })\n\n # Average Score\n output$avg_score <- renderText({\n filtered_data <- sample_data() %>%\n filter(course == input$course)\n sprintf(\"%.1f%%\", mean(filtered_data$score))\n })\n\n # Active Students\n output$active_students <- renderText({\n sample_size <- sample(100:200, 1) # Simulated active students count\n sprintf(\"%d\", sample_size)\n })\n\n # Performance Plot\n output$performance_plot <- renderPlot({\n filtered_data <- sample_data() %>%\n filter(course == input$course)\n \n ggplot(filtered_data, aes(x = date, y = score)) +\n geom_line(color = \"#007bff\") +\n geom_smooth(method = \"loess\", se = FALSE, color = \"#dc3545\") +\n theme_minimal() +\n labs(x = \"Date\", y = \"Score\", title = \"Performance Over Time\") +\n theme(plot.title = element_text(hjust = 0.5))\n })\n\n # Engagement Plot\n output$engagement_plot <- renderPlot({\n filtered_data <- sample_data() %>%\n filter(course == input$course)\n \n ggplot(filtered_data, aes(x = date, y = engagement)) +\n geom_area(fill = \"#28a745\", alpha = 0.5) +\n geom_line(color = \"#28a745\") +\n theme_minimal() +\n labs(x = \"Date\", y = \"Engagement Level\", title = \"Student Engagement Trends\") +\n theme(plot.title = element_text(hjust = 0.5))\n })\n\n # Progress Table\n output$progress_table <- renderTable({\n data.frame(\n Metric = c(\"Completion Rate\", \"Average Time per Session\", \"Success Rate\", \"Participation Score\"),\n Value = c(\"87%\", \"45 mins\", \"92%\", \"8.5/10\")\n )\n })\n}", "ui.R": "library(shiny)\nlibrary(bslib)\n\nui <- page_sidebar(\n title = \"EdTech Analytics Dashboard\",\n sidebar = sidebar(\n selectInput(\"course\", \"Select Course\", \n choices = c(\"Mathematics\", \"Science\", \"English\", \"History\")),\n selectInput(\"metric\", \"Select Metric\",\n choices = c(\"Student Engagement\", \"Performance\", \"Time Spent\", \"Completion Rate\")),\n checkboxGroupInput(\"filters\", \"Additional Filters\",\n choices = c(\"By Grade Level\", \"By Learning Style\", \"By Difficulty\"))\n ),\n layout_column_wrap(\n width = 1/2,\n value_box(\n title = \"Average Score\",\n value = textOutput(\"avg_score\"),\n theme = \"primary\"\n ),\n value_box(\n title = \"Active Students\",\n value = textOutput(\"active_students\"),\n theme = \"secondary\"\n )\n ),\n card(\n card_header(\"Performance Trends\"),\n plotOutput(\"performance_plot\")\n ),\n card(\n card_header(\"Student Engagement Analysis\"),\n plotOutput(\"engagement_plot\")\n ),\n card(\n card_header(\"Learning Progress\"),\n div(class = \"p-3\",\n tableOutput(\"progress_table\")\n )\n )\n)", "install.R": "install.packages('bslib')\ninstall.packages('dplyr')\ninstall.packages('ggplot2')\ninstall.packages('magrittr')\ninstall.packages('shiny')", "startApp.R": "\nlibrary(shiny)\noptions(shiny.host = '0.0.0.0')\noptions(shiny.port = 80)\nrunApp('app.R')\n"}