count_resp() is a generic function that count responses per student from Moodle Responses report(s) (not Grades report).
Similar to combine_resp(), if the Moodle responses report has response column(s) that contained embedded answers (Cloze),
you have an option to count them as a whole (1 Cloze column = 1 count) or as individual parts (count each parts of Cloze column, individually).
Other functionality are similar to check_sub() such as: encode & filter student's attempts by state (i.e., "Finished" or "In progress") and started time ("Started on" column),
cleans column names for easy manipulation, extracts student ID from "Email address", and unites "First name" and "Surname" column into "Name".
Usage
count_resp(
data,
extract_id_from = c("Email address", "Institution", "Department", "ID number"),
id_regex = ".*",
sep_name = " ",
state = c("Finished", "In progress"),
encode = c(1, 0),
choose_encode = c("max", "min", "all"),
choose_time = c("first", "last", "all"),
count_cloze_parts = F,
filter_count = c("max", "all"),
sep_col = "_"
)Arguments
- data
A data.frame or named list of data.frame of Moodle Responses report(s) (not Grades report)
- extract_id_from
(Character) Choose 1 column to extract ID from
- id_regex
(Character) A regular expression used to extract ID from column "Email address" in the Moodle Quiz report. The default is "
.*" meaning all characters. If your student email addresses has numeric IDs in them, try "[:digit:]+" to extract digits from the email. Note: Regular expression syntax is the same as stringr.- sep_name
A character in the new "Name" column that separate original "First name" and "Surname".
- state
A character vector to match values in "State" column of the Moodle Quiz report
- encode
An encoding numeric vector corresponding to
state. For example: by default, in the "State" column, "Finished" values will be encoded as1, and "In progress" will be encoded as0.- choose_encode
A character to filter student's attempt by the
encodeing."max" (default): return rows that have maximum encoding of each students.
"min": return rows that have minimum encoding of each students.
"all": no filter applied, return all rows.
- choose_time
A character to filter student's attempt by started time (determined by "Started on" column in Moodle Quiz report). This filter applies after
choose_encodehas been applied to the data."first" (default): return rows that represent first attempt of each students.
"last": return rows that represent last attempt of each students.
"all": no filter applied, return all rows after applying
choose_encode
- count_cloze_parts
(Logical) If a Moodle Responses report has at least one response column(s) that contained embedded answers (Cloze), set
count_cloze_parts = TRUEwill count individual parts of each Cloze columns. IfFALSE, then it will count each Cloze column as 1 count.- filter_count
(Character) One of "max" or "all". This filter option will apply after filter by
choose_encodeandchoose_time."max": filter rows that has maximum response count per student. If there are ≥ 1 rows, filter the first one based on
Started."all": No further filter apply.
- sep_col
(Character) If
datais a named list of data.frame,sep_colindicate a character separation between names of list and "State" or "Count_resp" columns.
Value
A data.frame, its output content is determined by class of its first argument: data.
If the
datais a data.frame; the output is an encoded, filtered, and cleaned data.frame of Moodle Responses report. And the "Count_resp" column is added with maximum number of count appended at the column name.If the
datais a named list of data.frame; the output is the same as previously described, but all Moodle Quiz reports are full-joined together by column "Name" and "ID". So that, "Count_resp" columns from each data.frame are sit together in a single data.frame, and "Total" column is added at the last column to indicate total count.
Details
Counting Mechanism:
count_resp() gives 1 count to 1 responses cell if one or more characters were found.
Blank or "-" (dash) response will not be counted.
Examples
# Count Responses of Quiz 1
count_resp(responses_ls$Quiz_1,
id_regex = "[:digit:]+")
#> # A tibble: 26 × 9
#> Name ID Insti…¹ Depar…² State Encode Started Grade…³ Count…⁴
#> <chr> <chr> <lgl> <lgl> <chr> <dbl> <dttm> <chr> <int>
#> 1 Lance… 004 NA NA Fini… 1 2022-04-19 19:19:00 Not ye… 2
#> 2 Sydne… 002 NA NA Fini… 1 2022-04-19 16:32:00 Not ye… 2
#> 3 Itzel… 016 NA NA Fini… 1 2022-04-19 12:36:00 Not ye… 1
#> 4 Hakam… 001 NA NA Fini… 1 2022-04-19 06:46:00 Not ye… 2
#> 5 Hamoo… 012 NA NA Fini… 1 2022-04-19 03:23:00 Not ye… 2
#> 6 Domin… 007 NA NA Fini… 1 2022-04-19 09:03:00 Not ye… 2
#> 7 Zhjad… 009 NA NA Fini… 1 2022-04-19 02:17:00 Not ye… 2
#> 8 Jorda… 013 NA NA Fini… 1 2022-04-19 12:10:00 Not ye… 2
#> 9 Kevin… 025 NA NA Fini… 1 2022-04-19 03:41:00 Not ye… 2
#> 10 Angel… 018 NA NA Fini… 1 2022-04-19 01:48:00 Not ye… 2
#> # … with 16 more rows, and abbreviated variable names ¹Institution,
#> # ²Department, ³Grade_2.00, ⁴Count_Resp_2
# Count Responses from All Quizzes
count_resp(responses_ls,
id_regex = "[:digit:]+")
#> # A tibble: 26 × 7
#> Name ID Quiz_1_State Quiz_1_Count_Re…¹ Quiz_…² Quiz_…³ Total_5
#> <chr> <chr> <chr> <int> <chr> <int> <int>
#> 1 Lance Xiong 004 Finished 2 Finish… 3 5
#> 2 Sydney Halamicek 002 Finished 2 Finish… 3 5
#> 3 Itzel Palomino 016 Finished 1 Finish… 3 4
#> 4 Hakam el-Farooq 001 Finished 2 Finish… 3 5
#> 5 Hamood al-Farha 012 Finished 2 Finish… 3 5
#> 6 Dominique Solis 007 Finished 2 Finish… 3 5
#> 7 Zhjade Alarid 009 Finished 2 Finish… 2 4
#> 8 Jordan Tan 013 Finished 2 Finish… 2 4
#> 9 Kevin Vasquez 025 Finished 2 Finish… 3 5
#> 10 Angela Carrillo 018 Finished 2 Finish… 2 4
#> # … with 16 more rows, and abbreviated variable names ¹Quiz_1_Count_Resp_2,
#> # ²Quiz_2_State, ³Quiz_2_Count_Resp_3