3.5 Training and Communication
49
“Upon successfully completing σ 1 , participants can σ 2
with respect to σ 3
by doing σ 4 ;
for example, σ 5 .
(3.9)
Therein, σ 1 is the course or training material (carrier) for which a learning outcome is
stated. The individuals σ 2 , σ 3 , σ 4 and σ 5 are specifiers (otras:specifier) of the learning
outcome:
• σ 2 specifies the operator of the learning outcome (concept otras:operator_specifier); a catalogue of operators with three-digit operator codes is included.
• σ 3 specifies the operand of the learning outcome (concept otras:operand_specifier);
the operand can be formulated in terms of one or multiple topics, for which fourdigit topic codes are given in OTRAS.
• σ 4 specifies the implementation (concept otras:implementation_specifier),
describing how the competency is carried out in practice (e.g. “by writing C++
codes” or “by carrying out appropriate series of MD simulations”); this specifier
is optional.
• σ 5 specifies an example (concept otras:example_specifier), illustrating how the
competency might be applied to a particular special case (e.g. “if asked to develop
a molecular model for caffeine, one might choose to parameterize a rigid coarsegrained model consisting of multiple Mie interaction sites”). This specifier is also
optional.
The operator specifier σ 2 indicates what sort of activity is enabled by possessing a
certain competency. Learning outcomes in course syllabi are typically formulated
concisely, e.g. “the students will be able to apply statistical mechanics to problems
from fluid phase thermodynamics.” In this example, the operator is expressed by the
predicate “apply.” In the interest of the legibility of a syllabus (and the work involved
in writing it), a precise definition of the meaning of the operator specifier is usually
not provided, and the interpretation is left to the intuition of the reader.
In the interest of platform and institutional interoperability between training
providers, it can nonetheless be helpful to reach an agreement on a more precise
specification of the semantics associated with a learning outcome formulation. This
has aspects of both semantic and pragmatic interoperabilities, such as where multiple instructors are expected to abide by the same syllabus and/or conduct exams that
confirm the success of the learning effort at a specified level. It may also support
the automated rendition of a syllabus in multiple languages. For this task, OTRAS
relies on a catalogue of operators disseminated by the German Kultusministerkonferenz (KMK), facilitating the specification of learning outcomes in the natural sciences in a consistent way [36]. In OTRAS, each operator has a three-digit topic
code (e.g. 235) and otras:is_expressed_by a concise predicate (e.g. “apply”), while
otras:is_defined_by gives a more detailed explanation of its meaning; in the given
case, “use a known idea, equation, principle, theory or law in a new situation” [36].
The KMK operators roughly correspond to elementary (operator codes 1xx), inter-
49
“Upon successfully completing σ 1 , participants can σ 2
with respect to σ 3
by doing σ 4 ;
for example, σ 5 .
(3.9)
Therein, σ 1 is the course or training material (carrier) for which a learning outcome is
stated. The individuals σ 2 , σ 3 , σ 4 and σ 5 are specifiers (otras:specifier) of the learning
outcome:
• σ 2 specifies the operator of the learning outcome (concept otras:operator_specifier); a catalogue of operators with three-digit operator codes is included.
• σ 3 specifies the operand of the learning outcome (concept otras:operand_specifier);
the operand can be formulated in terms of one or multiple topics, for which fourdigit topic codes are given in OTRAS.
• σ 4 specifies the implementation (concept otras:implementation_specifier),
describing how the competency is carried out in practice (e.g. “by writing C++
codes” or “by carrying out appropriate series of MD simulations”); this specifier
is optional.
• σ 5 specifies an example (concept otras:example_specifier), illustrating how the
competency might be applied to a particular special case (e.g. “if asked to develop
a molecular model for caffeine, one might choose to parameterize a rigid coarsegrained model consisting of multiple Mie interaction sites”). This specifier is also
optional.
The operator specifier σ 2 indicates what sort of activity is enabled by possessing a
certain competency. Learning outcomes in course syllabi are typically formulated
concisely, e.g. “the students will be able to apply statistical mechanics to problems
from fluid phase thermodynamics.” In this example, the operator is expressed by the
predicate “apply.” In the interest of the legibility of a syllabus (and the work involved
in writing it), a precise definition of the meaning of the operator specifier is usually
not provided, and the interpretation is left to the intuition of the reader.
In the interest of platform and institutional interoperability between training
providers, it can nonetheless be helpful to reach an agreement on a more precise
specification of the semantics associated with a learning outcome formulation. This
has aspects of both semantic and pragmatic interoperabilities, such as where multiple instructors are expected to abide by the same syllabus and/or conduct exams that
confirm the success of the learning effort at a specified level. It may also support
the automated rendition of a syllabus in multiple languages. For this task, OTRAS
relies on a catalogue of operators disseminated by the German Kultusministerkonferenz (KMK), facilitating the specification of learning outcomes in the natural sciences in a consistent way [36]. In OTRAS, each operator has a three-digit topic
code (e.g. 235) and otras:is_expressed_by a concise predicate (e.g. “apply”), while
otras:is_defined_by gives a more detailed explanation of its meaning; in the given
case, “use a known idea, equation, principle, theory or law in a new situation” [36].
The KMK operators roughly correspond to elementary (operator codes 1xx), inter-